Transformer-in-Vision

Recent Transformer-based CV and related works. Welcome to comment/contribute!

The transformer is now a basic component, adopted in nearly all AI models. Keep updated --> updated irregularly.

New Hope: LLM-in-Vision

Resource

• ChatGPT for Robotics: Design Principles and Model Abilities, [Paper], [Code]

• DIFFUSIONDB [Page], [Paper]

• LAION-5B [Page], [Paper]

• LAVIS [Page], [Paper]

• Imagen Video [Page], [Paper]

• Phenaki [Page], [Paper]

• DREAMFUSION [Page], [Paper]

• MAKE-A-VIDEO [Page], [Paper]

• Stable Difffusion [Page], [Paper]

• NUWA-Infinity [Page], [Paper]

• Parti [Page], [Code]

• Imagen [Page], [Paper]

• Gato: A Generalist Agent, [Paper]

• PaLM: Scaling Language Modeling with Pathways, [Paper]

• DALL·E 2 [Page], [Paper]

• SCENIC: A JAX Library for Computer Vision Research and Beyond, [Code]

• V-L joint learning study (with good tables): [METER], [Kaleido-BERT]

• Attention is all you need, [Paper]

• CLIP [Page], [Paper], [Code], [arXiv]

• DALL·E [Page], [Code], [Paper]

• huggingface/transformers

• Kyubyong/transformer, TF

• jadore801120/attention-is-all-you-need-pytorch, Torch

• krasserm/fairseq-image-captioning

• PyTorch Transformers Tutorials

• ictnlp/awesome-transformer

• basicv8vc/awesome-transformer

• dk-liang/Awesome-Visual-Transformer

• yuewang-cuhk/awesome-vision-language-pretraining-papers

Survey

• (arXiv 2023.2) TRANSFORMER-BASED SENSOR FUSION FOR AUTONOMOUS DRIVING: A SURVEY, [Paper], [Page]

• (arXiv 2023.2) Deep Learning for Video-Text Retrieval: a Review, [Paper]

• (arXiv 2023.2) Large-scale Multi-Modal Pre-trained Models: A Comprehensive Survey, [Paper]

• (arXiv 2023.2) Transformer-based Generative Adversarial Networks in Computer Vision: A Comprehensive Survey, [Paper]

• (arXiv 2023.2) Knowledge Distillation in Vision Transformers: A Critical Review, [Paper]

• (arXiv 2023.2) A Survey on Efficient Training of Transformers, [Paper]

• (arXiv 2023.1) ChatGPT is not all you need. A State of the Art Review of large Generative AI models, [Paper]

• (arXiv 2022.12) Transformers in Action Recognition: A Review on Temporal Modeling, [Paper]

• (arXiv 2022.11) Vision Transformers in Medical Imaging: A Review, [Paper]

• (arXiv 2022.11) A survey on knowledge-enhanced multimodal learning, [Paper]

• (arXiv 2022.10) Vision-Language Pre-training: Basics, Recent Advances, and Future Trends, [Paper]

• (arXiv 2022.10) A Survey on Graph Neural Networks and Graph Transformers in Computer Vision: A Task-Oriented Perspective, [Paper]

• (arXiv 2022.09) VISION TRANSFORMERS FOR ACTION RECOGNITION: A SURVEY, [Paper]

• (arXiv 2022.09) Transformers in Remote Sensing: A Survey, [Paper], [Code]

• (arXiv 2022.08) 3D Vision with Transformers: A Survey, [Paper], [Code]

• (arXiv 2022.08) A Survey on Masked Autoencoder for Self-supervised Learning in Vision and Beyond, [Paper]

• (arXiv 2022.07) Vision Transformers: State of the Art and Research Challenges, [Paper]

• (arXiv 2022.07) SELF-SUPERVISED LEARNING FOR VIDEOS: A SURVEY, [Paper]

• (arXiv 2022.06) Multimodal Learning with Transformers: A Survey, [Paper]

• (arXiv 2022.05) Vision Transformer: Vit and its Derivatives, [Paper]

• (arXiv 2022.05) Transformers in 3D Point Clouds: A Survey, [Paper]

• (arXiv 2022.04) Visual Attention Methods in Deep Learning: An In-Depth Survey, [Paper]

• (arXiv 2022.04) Vision-and-Language Pretrained Models: A Survey, [Paper]

• (arXiv 2022.03) A Roadmap for Big Model, [Paper]

• (arXiv 2022.03) Transformers Meet Visual Learning Understanding: A Comprehensive Review, [[Paper]](https://arxiv.org/pdf/2203.12944.pdf）

• (arXiv 2022.03) Recent Advances in Vision Transformer: A Survey and Outlook of Recent Work, [Paper], [Project]

• (arXiv 2022.02) A Survey of Vision-Language Pre-Trained Models, [Paper]

• (arXiv 2022.02) VLP: A Survey on Vision-Language Pre-training, [Paper]

• (arXiv 2022.02) Transformer for Graphs: An Overview from Architecture Perspective, [Paper]

• (arXiv 2022.01) Video Transformers: A Survey, [Paper]

• (arXiv 2021.11) ARE WE READY FOR A NEW PARADIGM SHIFT? A SURVEY ON VISUAL DEEP MLP, [Paper]

• (arXiv 2021.11) A Survey of Visual Transformers, [Paper]

• (arXiv 2021.09) Survey: Transformer based Video-Language Pre-training, [Paper]

• (arXiv 2021.06) A Survey of Transformers, [Paper]

• (arXiv 2021.06) Attention mechanisms and deep learning for machine vision: A survey of the state of the art, [Paper]

• (arXiv 2021.06) Pre-Trained Models: Past, Present and Future, [Paper]

• (arXiv 2021.05) Can Attention Enable MLPs To Catch Up With CNNs? [Paper]

• (arXiv 2021.03) A Practical Survey on Faster and Lighter Transformers, [Paper]

• (arXiv 2021.03) Perspectives and Prospects on Transformer Architecture for Cross-Modal Tasks with Language and Vision, [Paper]

• (arXiv 2021.01) A Survey on Visual Transformer, [Paper]

• (arXiv 2020.9) Efficient Transformers: A Survey, [Paper]

• (arXiv 2020.1) Transformers in Vision: A Survey, [Paper]

Recent Papers

2023.8

• (arXiv 2023.8) VL-PET: Vision-and-Language Parameter-Efficient Tuning via Granularity Control, [Paper], [Project]

2023.5

• (arXiv 2023.5) Understanding Gaussian Attention Bias of Vision Transformers Using Effective Receptive Fields, [Paper]

2023.3

• (arXiv 2023.3) Query-Dependent Video Representation for Moment Retrieval and Highlight Detection, [Paper], [Code]

2023.2

• (arXiv 2023.2) Open-domain Visual Entity Recognition: Towards Recognizing Millions of Wikipedia Entities, [Paper]

• (arXiv 2023.2) KS-DETR: Knowledge Sharing in Attention Learning for Detection Transformer, [Paper], [Code]

• (arXiv 2023.2) HUMAN MOTIONFORMER: TRANSFERRING HUMAN MOTIONS WITH VISION TRANSFORMERS, [Paper], [Code]

• (arXiv 2023.2) Aligning Text-to-Image Models using Human Feedback, [Paper]

• (arXiv 2023.2) Controlled and Conditional Text to Image Generation with Diffusion Prior, [Paper]

• (arXiv 2023.2) Can Pre-trained Vision and Language Models Answer Visual Information-Seeking Questions? [Paper], [Code]

• (arXiv 2023.2) OBJECT-CENTRIC VIDEO PREDICTION VIA DECOUPLING OF OBJECT DYNAMICS AND INTERACTIONS, [Paper], [Project]

• (arXiv 2023.2) Distribution Normalization: An “Effortless” Test-Time Augmentation for Contrastively Learned Visual-language Models, [Paper], [Code]

• (arXiv 2023.2) Teaching CLIP to Count to Ten, [Paper], [Project]

• (arXiv 2023.2) Designing an Encoder for Fast Personalization of Text-to-Image Models, [Paper], [Project]

• (arXiv 2023.2) Side Adapter Network for Open-Vocabulary Semantic Segmentation, [Paper], [Code]

• (arXiv 2023.2) Learning Visual Representations via Language-Guided Sampling, [Paper]

• (arXiv 2023.2) VoxFormer: Sparse Voxel Transformer for Camera-based 3D Semantic Scene Completion, [Paper], [Code]

• (arXiv 2023.2) Language-Driven Representation Learning for Robotics, [Paper], [Project]

• (arXiv 2023.2) A Convolutional Vision Transformer for Semantic Segmentation of Side-Scan Sonar Data, [Paper], [Code]

• (arXiv 2023.2) Lightweight Real-time Semantic Segmentation Network with Efficient Transformer and CNN, [Paper], [Code]

• (arXiv 2023.2) VIEWCO: DISCOVERING TEXT-SUPERVISED SEGMENTATION MASKS VIA MULTI-VIEW SEMANTIC CONSISTENCY, [Paper], [Code]

• (arXiv 2023.2) CertViT: Certified Robustness of Pre-Trained Vision Transformers, [Paper], [Code]

• (arXiv 2023.2) Paparazzi: A Deep Dive into the Capabilities of Language and Vision Models for Grounding Viewpoint Descriptions, [Paper]

• (arXiv 2023.2) MaskedKD: Efficient Distillation of Vision Transformers with Masked Images, [Paper]

• (arXiv 2023.2) A General Visual Representation Guided Framework with Global Affinity for Weakly Supervised Salient Object Detection, [Paper]

• (arXiv 2023.2) ViTA: A Vision Transformer Inference Accelerator for Edge Applications, [Paper]

• (arXiv 2023.2) Video Action Recognition Collaborative Learning with Dynamics via PSO-ConvNet Transformer, [Paper], [Code]

• (arXiv 2023.2) A Pilot Evaluation of ChatGPT and DALL-E 2 on Decision Making and Spatial Reasoning, [Paper]

• (arXiv 2023.2) StyLIP: Multi-Scale Style-Conditioned Prompt Learning for CLIP-based Domain Generalization, [Paper]

• (arXiv 2023.2) Meta Style Adversarial Training for Cross-Domain Few-Shot Learning, [Paper]

• (arXiv 2023.2) HYNETER: HYBRID NETWORK TRANSFORMER FOR OBJECT DETECTION, [Paper]

• (arXiv 2023.2) STOA-VLP: Spatial-Temporal Modeling of Object and Action for Video-Language Pre-training, [Paper]

• (arXiv 2023.2) Constraint and Union for Partially-Supervised Temporal Sentence Grounding, [Paper]

• (arXiv 2023.2) STB-VMM: Swin Transformer Based Video Motion Magnification, [Paper]

• (arXiv 2023.2) Fashion Image Retrieval with Multi-Granular Alignment, [Paper]

• (arXiv 2023.2) LayoutDiffuse: Adapting Foundational Diffusion Models for Layout-to-Image Generation, [Paper]

• (arXiv 2023.2) CK-Transformer: Commonsense Knowledge Enhanced Transformers for Referring Expression Comprehension, [Paper], [Code]

• (arXiv 2023.2) MaskSketch: Unpaired Structure-guided Masked Image Generation, [Paper]

• (arXiv 2023.2) Single Motion Diffusion, [Paper], [Code]

• (arXiv 2023.2) Tri-Perspective View for Vision-Based 3D Semantic Occupancy Prediction, [Paper], [Code]

• (arXiv 2023.2) ANSEL Photobot: A Robot Event Photographer with Semantic Intelligence, [Paper]

• (arXiv 2023.2) ForceFormer: Exploring Social Force and Transformer for Pedestrian Trajectory Prediction, [Paper]

• (arXiv 2023.2) Video Probabilistic Diffusion Models in Projected Latent Space, [Paper]

• (arXiv 2023.2) Dataset Interfaces: Diagnosing Model Failures Using Controllable Counterfactual Generation, [Paper], [Code]

• (arXiv 2023.2) Learning to Substitute Ingredients in Recipes, [Paper]

• (arXiv 2023.2) Energy Transformer, [Paper]

• (arXiv 2023.2) Efficiency 360: Efficient Vision Transformers, [Paper]

• (arXiv 2023.2) A-la-carte Prompt Tuning (APT): Combining Distinct Data Via Composable ` Prompting, [Paper]

• (arXiv 2023.2) Effective Data Augmentation With Diffusion Models, [Paper], [Project]

• (arXiv 2023.2) PRedItOR: Text Guided Image Editing with Diffusion Prior, [Paper]

• (arXiv 2023.2) TcGAN: Semantic-Aware and Structure-Preserved GANs with Individual Vision Transformer for Fast Arbitrary One-Shot Image Generation, [Paper]

• (arXiv 2023.2) Hierarchical Cross-modal Transformer for RGB-D Salient Object Detection, [Paper]

• (arXiv 2023.2) MINOTAUR: Multi-task Video Grounding From Multimodal Queries, [Paper]

• (arXiv 2023.2) Towards Efficient Visual Adaption via Structural Re-parameterization, [Paper], [Code]

• (arXiv 2023.2) Efficient 3D Object Reconstruction using Visual Transformers, [Paper]

• (arXiv 2023.2) Retrieval-augmented Image Captioning, [Paper]

• (arXiv 2023.2) Robust Human Motion Forecasting using Transformer-based Model, [Paper]

• (arXiv 2023.2) VQ3D: Learning a 3D-Aware Generative Model on ImageNet, [Paper], [Project]

• (arXiv 2023.2) UKnow: A Unified Knowledge Protocol for Common-Sense Reasoning and Vision-Language Pre-training, [Paper], [Code]

• (arXiv 2023.2) A THEORETICAL UNDERSTANDING OF SHALLOW VISION TRANSFORMERS: LEARNING, GENERALIZATION, AND SAMPLE COMPLEXITY, [Paper]

• (arXiv 2023.2) A Simple Zero-shot Prompt Weighting Technique to Improve Prompt Ensembling in Text-Image Models, [Paper]

• (arXiv 2023.2) Generalized Few-Shot Continual Learning with Contrastive Mixture of Adapters, [Paper], [Code]

• (arXiv 2023.2) Actional Atomic-Concept Learning for Demystifying Vision-Language Navigation, [Paper]

• (arXiv 2023.2) Towards Local Visual Modeling for Image Captioning, [Paper], [Code]

• (arXiv 2023.2) CLIP-RR: IMPROVED CLIP NETWORK FOR RELATION-FOCUSED CROSS-MODAL INFORMATION RETRIEVAL, [Paper]

• (arXiv 2023.2) Anticipating Next Active Objects for Egocentric Videos, [Paper], [Code]

• (arXiv 2023.2) UniAdapter: Unified Parameter-Efficient Transfer Learning for Cross-modal Modeling, [Paper], [Code]

• (arXiv 2023.2) TEAM DETR: GUIDE QUERIES AS A PROFESSIONAL TEAM IN DETECTION TRANSFORMERS, [Paper], [Code]

• (arXiv 2023.2) ConceptFusion: Open-set Multimodal 3D Mapping, [Paper], [Project]

• (arXiv 2023.2) Team Triple-Check at Factify 2: Parameter-Efficient Large Foundation Models with Feature Representations for Multi-Modal Fact Verification, [Paper], [Code]

• (arXiv 2023.2) PolyFormer: Referring Image Segmentation as Sequential Polygon Generation, [Paper]

• (arXiv 2023.2) Pose-Oriented Transformer with Uncertainty-Guided Refinement for 2D-to-3D Human Pose Estimation, [Paper]

• (arXiv 2023.2) TFormer: A Transmission-Friendly ViT Model for IoT Devices, [Paper], [Code]

• (arXiv 2023.2) Tri-Perspective View for Vision-Based 3D Semantic Occupancy Prediction, [Paper], [Code]

• (arXiv 2023.2) Adding Conditional Control to Text-to-Image Diffusion Models, [Paper], [Code]

• (arXiv 2023.2) Invariant Slot Attention: Object Discovery with Slot-Centric Reference Frames, [Paper]

• (arXiv 2023.2) IS MULTI-MODAL VISION SUPERVISION BENEFICIAL TO LANGUAGE? [Paper]

• (arXiv 2023.2) Data-Driven Stochastic Motion Evaluation and Optimization with Image by Spatially-Aligned Temporal Encoding, [Paper]

• (arXiv 2023.2) Scaling Vision Transformers to 22 Billion Parameters, [Paper]

• (arXiv 2023.2) Adapting Pre-trained Vision Transformers from 2D to 3D through Weight Inflation Improves Medical Image Segmentation, [Paper], [Code]

• (arXiv 2023.2) Mitigating Bias in Visual Transformers via Targeted Alignment, [Paper]

• (arXiv 2023.2) IH-ViT: Vision Transformer-based Integrated Circuit Appearance Defect Detection, [Paper]

• (arXiv 2023.2) Re-ViLM: Retrieval-Augmented Visual Language Model for Zero and Few-Shot Image Captioning, [Paper]

• (arXiv 2023.2) Learning by Asking for Embodied Visual Navigation and Task Completion, [Paper]

• (arXiv 2023.2) Reversible Vision Transformers, [Paper], [Code1], [Code2]

• (arXiv 2023.2) Neural Congealing: Aligning Images to a Joint Semantic Atlas, [Paper], [Project]

• (arXiv 2023.2) Adversarial Prompting for Black Box Foundation Models, [Paper]

• (arXiv 2023.2) Understanding Why ViT Trains Badly on Small Datasets: An Intuitive Perspective, [Paper], [Code]

• (arXiv 2023.2) CROSS-LAYER RETROSPECTIVE RETRIEVING VIA LAYER ATTENTION, [Paper], [Code]

• (arXiv 2023.2) Convolutional Neural Networks Trained to Identify Words Provide a Good Account of Visual Form Priming Effects, [Paper]

• (arXiv 2023.2) Zero-shot Generation of Coherent Storybook from Plain Text Story using Diffusion Models, [Paper]

• (arXiv 2023.2) OSRT: Omnidirectional Image Super-Resolution with Distortion-aware Transformer, [Paper]

• (arXiv 2023.2) Pic2Word: Mapping Pictures to Words for Zero-shot Composed Image Retrieval, [Paper], [Code]

• (arXiv 2023.2) SimCon Loss with Multiple Views for Text Supervised Semantic Segmentation, [Paper]

• (arXiv 2023.2) PhysFormer++: Facial Video-based Physiological Measurement with SlowFast Temporal Difference Transformer, [Paper]

• (arXiv 2023.2) Scaling Self-Supervised End-to-End Driving with Multi-View Attention Learning, [Paper]

• (arXiv 2023.2) HumanMAC: Masked Motion Completion for Human Motion Prediction, [Paper], [Project]

• (arXiv 2023.2) LAMPP: Language Models as Probabilistic Priors for Perception and Action, [Paper]

• (arXiv 2023.2) Zero-Shot Robot Manipulation from Passive Human Videos, [Paper], [Project]

• (arXiv 2023.2) MixFormer: End-to-End Tracking with Iterative Mixed Attention, [Paper], [Code]

• (arXiv 2023.2) LexLIP: Lexicon-Bottlenecked Language-Image Pre-Training for Large-Scale Image-Text Retrieval, [Paper]

• (arXiv 2023.2) V1T: large-scale mouse V1 response prediction using a Vision Transformer, [Paper]

• (arXiv 2023.2) AIM: ADAPTING IMAGE MODELS FOR EFFICIENT VIDEO ACTION RECOGNITION, [Paper], [Project]

• (arXiv 2023.2) KDEformer: Accelerating Transformers via Kernel Density Estimation, [Paper], [Code]

• (arXiv 2023.2) Semantic-Guided Image Augmentation with Pre-trained Models, [Paper]

• (arXiv 2023.2) X-ReID: Cross-Instance Transformer for Identity-Level Person Re-Identification, [Paper]

• (arXiv 2023.2) MOMA: Distill from Self-Supervised Teachers, [Paper]

• (arXiv 2023.2) Learning to Agree on Vision Attention for Visual Commonsense Reasoning, [Paper]

• (arXiv 2023.2) Efficient End-to-End Video Question Answering with Pyramidal Multimodal Transformer, [Paper], [Code]

• (arXiv 2023.2) LipFormer: Learning to Lipread Unseen Speakers based on Visual-Landmark Transformers, [Paper]

• (arXiv 2023.2) Oscillation-free Quantization for Low-bit Vision Transformers, [Paper]

• (arXiv 2023.2) Design Booster: A Text-Guided Diffusion Model for Image Translation with Spatial Layout Preservation, [Paper]

• (arXiv 2023.2) Contrast with Reconstruct: Contrastive 3D Representation Learning Guided by Generative Pretraining, [Paper], [Code]

• (arXiv 2023.2) Leaving Reality to Imagination: Robust Classification via Generated Datasets, [Paper], [Code]

• (arXiv 2023.2) CHiLS: Zero-Shot Image Classification with Hierarchical Label Sets, [Paper], [Code]

• (arXiv 2023.2) Zero-shot Image-to-Image Translation, [Paper], [Project]

• (arXiv 2023.2) Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers, [Paper]

• (arXiv 2023.2) EXPLICIT BOX DETECTION UNIFIES END-TO-END MULTI-PERSON POSE ESTIMATION, [Paper], [Code]

• (arXiv 2023.2) CFFT-GAN: Cross-domain Feature Fusion Transformer for Exemplar-based Image Translation, [Paper]

• (arXiv 2023.2) DEVICE: DEpth and VIsual ConcEpts Aware Transformer for TextCaps, [Paper]

• (arXiv 2023.2) CVTNet: A Cross-View Transformer Network for Place Recognition Using LiDAR Data, [Paper], [Code]

• (arXiv 2023.2) DilateFormer: Multi-Scale Dilated Transformer for Visual Recognition, [Paper], [Code]

• (arXiv 2023.2) HDFormer: High-order Directed Transformer for 3D Human Pose Estimation, [Paper], [Code]

• (arXiv 2023.2) IC^3: Image Captioning by Committee Consensus, [Paper], [Code]

• (arXiv 2023.2) Boosting Low-Data Instance Segmentation by Unsupervised Pre-training with Saliency Prompt, [Paper]

• (arXiv 2023.2) QR-CLIP: Introducing Explicit Open-World Knowledge for Location and Time Reasoning, [Paper]

• (arXiv 2023.2) Vision Transformer-based Feature Extraction for Generalized Zero-Shot Learning, [Paper]

• (arXiv 2023.2) Multimodal Chain-of-Thought Reasoning in Language Models, [Paper], [Code]

• (arXiv 2023.2) CLIPood: Generalizing CLIP to Out-of-Distributions, [Paper]

• (arXiv 2023.2) Language Quantized AutoEncoders: Towards Unsupervised Text-Image Alignment, [Paper]

• (arXiv 2023.2) The geometry of hidden representations of large transformer models, [Paper]

• (arXiv 2023.2) Debiasing Vision-Language Models via Biased Prompts, [Paper], [Code]

• (arXiv 2023.2) COMPOSITIONAL PROMPT TUNING WITH MOTION CUES FOR OPEN-VOCABULARY VIDEO RELATION DETECTION, [Paper], [Code]

• (arXiv 2023.2) mPLUG-2: A Modularized Multi-modal Foundation Model Across Text, Image and Video, [Paper], [Code]

• (arXiv 2023.2) Transforming CLIP to an Open-vocabulary Video Model via Interpolated Weight Optimization, [Paper]

• (arXiv 2023.2) ADAPT: Action-aware Driving Caption Transformer, [Paper], [Code]

2023.1

• (arXiv 2023.1) AdaPoinTr: Diverse Point Cloud Completion with Adaptive Geometry-Aware Transformers, [Paper], [Code]

• (arXiv 2023.1) EXIF as Language: Learning Cross-Modal Associations Between Images and Camera Metadata, [Paper], [Project]

• (arXiv 2023.1) Head-Free Lightweight Semantic Segmentation with Linear Transformer, [Paper], [Code]

• (arXiv 2023.1) Geometry-biased Transformers for Novel View Synthesis, [Paper], [Project]

• (arXiv 2023.1) Continual Few-Shot Learning Using HyperTransformers, [Paper]

• (arXiv 2023.1) SEMPPL: PREDICTING PSEUDO-LABELS FOR BETTER CONTRASTIVE REPRESENTATIONS, [Paper]

• (arXiv 2023.1) Learning to Summarize Videos by Contrasting Clips, [Paper]

• (arXiv 2023.1) Guiding Text-to-Image Diffusion Model Towards Grounded Generation, [Paper], [Project]

• (arXiv 2023.1) Domain Expansion of Image Generators, [Paper], [Code]

• (arXiv 2023.1) Scene-centric vs. Object-centric Image-Text Cross-modal Retrieval: A Reproducibility Study, [Paper]

• (arXiv 2023.1) Tracr: Compiled Transformers as a Laboratory for Interpretability, [Paper], [Code]

• (arXiv 2023.1) CLIP the Gap: A Single Domain Generalization Approach for Object Detection, [Paper]

• (arXiv 2023.1) Text to Point Cloud Localization with Relation-Enhanced Transformer, [Paper]

• (arXiv 2023.1) GOHSP: A Unified Framework of Graph and Optimization-based Heterogeneous Structured Pruning for Vision Transformer, [Paper]

• (arXiv 2023.1) Toward Building General Foundation Models for Language, Vision, and Vision-Language Understanding Tasks, [Paper]

• (arXiv 2023.1) ViTs for SITS: Vision Transformers for Satellite Image Time Series, [Paper], [Code]

• (arXiv 2023.1) CLIP2Scene: Towards Label-efficient 3D Scene Understanding by CLIP, [Paper]

• (arXiv 2023.1) A Large-Scale Outdoor Multi-modal Dataset and Benchmark for Novel View Synthesis and Implicit Scene Reconstruction, [Paper], [Project]

• (arXiv 2023.1) USER: Unified Semantic Enhancement with Momentum Contrast for Image-Text Retrieval, [Paper], [Code]

• (arXiv 2023.1) SAT: Size-Aware Transformer for 3D Point Cloud Semantic Segmentation, [Paper]

• (arXiv 2023.1) Masked Visual Reconstruction in Language Semantic Space, [Paper], [Code]

• (arXiv 2023.1) Vision Learners Meet Web Image-Text Pairs, [Paper], [Code]

• (arXiv 2023.1) GLIGEN: Open-Set Grounded Text-to-Image Generation, [Paper], [Project]

• (arXiv 2023.1) Learning Customized Visual Models with Retrieval-Augmented Knowledge, [Paper], [Project]

• (arXiv 2023.1) UATVR: Uncertainty-Adaptive Text-Video Retrieval, [Paper]

• (arXiv 2023.1) Learning Aligned Cross-modal Representations for Referring Image Segmentation, [Paper]

• (arXiv 2023.1) T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations, [Paper], [Project]

• (arXiv 2023.1) DSVT: Dynamic Sparse Voxel Transformer with Rotated Sets, [Paper], [Code]

• (arXiv 2023.1) CMAE-V: Contrastive Masked Autoencoders for Video Action Recognition, [Paper]

• (arXiv 2023.1) Generating Templated Caption for Video Grounding, [Paper]

• (arXiv 2023.1) Dyna-DepthFormer: Multi-frame Transformer for Self-Supervised Depth Estimation in Dynamic Scenes, [Paper]

• (arXiv 2023.1) SwinDepth: Unsupervised Depth Estimation using Monocular Sequences via Swin Transformer and Densely Cascaded Network, [Paper]

• (arXiv 2023.1) CLIPTER: Looking at the Bigger Picture in Scene Text Recognition, [Paper]

• (arXiv 2023.1) Temporal Perceiving Video-Language Pre-training, [Paper]

• (arXiv 2023.1) Joint Representation Learning for Text and 3D Point Cloud, [Paper], [Code]

• (arXiv 2023.1) Effective End-to-End Vision Language Pretraining with Semantic Visual Loss, [Paper]

• (arXiv 2023.1) PTA-Det: Point Transformer Associating Point cloud and Image for 3D Object Detection, [Paper]

• (arXiv 2023.1) Face Recognition in the age of CLIP & Billion image datasets, [Paper]

• (arXiv 2023.1) HSTFormer: Hierarchical Spatial-Temporal Transformers for 3D Human Pose Estimation, [Paper], [Code]

• (arXiv 2023.1) Towards Models that Can See and Read, [Paper]

• (arXiv 2023.1) Embodied Agents for Efficient Exploration and Smart Scene Description, [Paper]

• (arXiv 2023.1) Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture, [Paper]

• (arXiv 2023.1) Revisiting the Spatial and Temporal Modeling for Few-shot Action Recognition, [Paper]

• (arXiv 2023.1) Multimodal Video Adapter for Parameter Efficient Video Text Retrieval, [Paper]

• (arXiv 2023.1) Self Supervision Does Not Help Natural Language Supervision at Scale, [Paper]

• (arXiv 2023.1) MULTI-TARGET MULTI-CAMERA VEHICLE TRACKING USING TRANSFORMER-BASED CAMERA LINK MODEL AND SPATIAL-TEMPORAL INFORMATION, [Paper]

• (arXiv 2023.1) ATMAN: Understanding Transformer Predictions Through Memory Efficient Attention Manipulation, [Paper]

• (arXiv 2023.1) DDS: Decoupled Dynamic Scene-Graph Generation Network, [Paper], [Code]

• (arXiv 2023.1) Visual Writing Prompts: Character-Grounded Story Generation with Curated Image Sequences, [Paper]

• (arXiv 2023.1) Image Memorability Prediction with Vision Transformers, [Paper]

• (arXiv 2023.1) HOLISTICALLY EXPLAINABLE VISION TRANSFORMERS, [Paper]

• (arXiv 2023.1) FlatFormer: Flattened Window Attention for Efficient Point Cloud Transformer, [Paper]

• (arXiv 2023.1) LEGO-Net: Learning Regular Rearrangements of Objects in Rooms, [Paper], [Project]

• (arXiv 2023.1) Zorro: the masked multimodal transformer, [Paper]

• (arXiv 2023.1) Towards Robust Video Instance Segmentation with Temporal-Aware Transformer, [Paper]

• (arXiv 2023.1) Learning Open-vocabulary Semantic Segmentation Models From Natural Language Supervision, [Paper], [Project]

• (arXiv 2023.1) Summarize the Past to Predict the Future: Natural Language Descriptions of Context Boost Multimodal Object Interaction Anticipation, [Paper], [Code]

• (arXiv 2023.1) Combined Use of Federated Learning and Image Encryption for Privacy-Preserving Image Classification with Vision Transformer, [Paper]

• (arXiv 2023.1) Slice Transformer and Self-supervised Learning for 6DoF Localization in 3D Point Cloud Maps, [Paper]

• (arXiv 2023.1) IMPROVING ACCURACY OF ZERO-SHOT ACTION RECOGNITION WITH HANDCRAFTED FEATURES, [Paper]

• (arXiv 2023.1) Learning to View: Decision Transformers for Active Object Detection, [Paper]

• (arXiv 2023.1) Visual Semantic Relatedness Dataset for Image Captioning, [Paper], [Code]

• (arXiv 2023.1) VERSATILE NEURAL PROCESSES FOR LEARNING IMPLICIT NEURAL REPRESENTATIONS, [Paper], [Code]

• (arXiv 2023.1) RangeViT: Towards Vision Transformers for 3D Semantic Segmentation in Autonomous Driving, [Paper], [Code]

• (arXiv 2023.1) Exploiting Optical Flow Guidance for Transformer-Based Video Inpainting, [Paper]

• (arXiv 2023.1) Image Super-Resolution using Efficient Striped Window Transformer, [Paper], [Code]

• (arXiv 2023.1) Out of Distribution Performance of State of Art Vision Model, [Paper], [Code]

• (arXiv 2023.1) Compact Transformer Tracker with Correlative Masked Modeling, [Paper], [Code]

• (arXiv 2023.1) Vision-Language Models Performing Zero-Shot Tasks Exhibit Gender-based Disparities, [Paper]

• (arXiv 2023.1) Cut and Learn for Unsupervised Object Detection and Instance Segmentation, [Paper], [Code]

• (arXiv 2023.1) Explaining Visual Biases as Words by Generating Captions, [Paper], [Code]

• (arXiv 2023.1) Revisiting Temporal Modeling for CLIP-based Image-to-Video Knowledge Transferring, [Paper], [Code]

• (arXiv 2023.1) Multi-video Moment Ranking with Multimodal Clue, [Paper]

• (arXiv 2023.1) SDF-FORMER: MONOCULAR SCENE RECONSTRUCTION WITH 3D SDF TRANSFORMERS, [Paper], [Project]

• (arXiv 2023.1) Grounding Language Models to Images for Multimodal Generation, [Paper]

• (arXiv 2023.1) Pseudo 3D Perception Transformer with Multi-level Confidence Optimization for Visual Commonsense Reasoning, [Paper]

• (arXiv 2023.1) A Modular Multi-stage Lightweight Graph Transformer Network for Human Pose and Shape Estimation from 2D Human Pose, [Paper]

• (arXiv 2023.1) Priors are Powerful: Improving a Transformer for Multi-camera 3D Detection with 2D Priors, [Paper]

• (arXiv 2023.1) UPop: Unified and Progressive Pruning for Compressing Vision-Language Transformers, [Paper]

• (arXiv 2023.1) Fairness-aware Vision Transformer via Debiased Self-Attention, [Paper]

• (arXiv 2023.1) Anchor-Based Adversarially Robust Zero-Shot Learning Driven by Language, [Paper]

• (arXiv 2023.1) Distilling Internet-Scale Vision-Language Models into Embodied Agents, [Paper]

• (arXiv 2023.1) 6-DoF Robotic Grasping with Transformer, [Paper]

• (arXiv 2023.1) Do Embodied Agents Dream of Pixelated Sheep?: Embodied Decision Making using Language Guided World Modelling, [Paper], [Project]

• (arXiv 2023.1) GALIP: Generative Adversarial CLIPs for Text-to-Image Synthesis, [Paper], [Code]

• (arXiv 2023.1) STAIR: Learning Sparse Text and Image Representation in Grounded Tokens, [Paper]

• (arXiv 2023.1) Aerial Image Object Detection With Vision Transformer Detector (ViTDet), [Paper]

• (arXiv 2023.1) Towards Vision Transformer Unrolling Fixed-Point Algorithm: a Case Study on Image Restoration, [Paper]

• (arXiv 2023.1) Debiased Fine-Tuning for Vision-language Models by Prompt Regularization, [Paper], [Code]

• (arXiv 2023.1) BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models, [Paper], [Code]

• (arXiv 2023.1) Tagging before Alignment: Integrating Multi-Modal Tags for Video-Text Retrieval, [Paper]

• (arXiv 2023.1) SEAFORMER: SQUEEZE-ENHANCED AXIAL TRANSFORMER FOR MOBILE SEMANTIC SEGMENTATION, [Paper], [Code]

• (arXiv 2023.1) Learning 6-DoF Fine-grained Grasp Detection Based on Part Affordance Grounding, [Paper], [Project]

• (arXiv 2023.1) Multimodal Event Transformer for Image-guided Story Ending Generation, [Paper]

• (arXiv 2023.1) Style-Aware Contrastive Learning for Multi-Style Image Captioning, [Paper]

• (arXiv 2023.1) 3DShape2VecSet: A 3D Shape Representation for Neural Fields and Generative Diffusion Models, [Paper]

• (arXiv 2023.1) Semi-Parametric Video-Grounded Text Generation, [Paper]

• (arXiv 2023.1) Robust Transformer with Locality Inductive Bias and Feature Normalization, [Paper]

• (arXiv 2023.1) LEVERAGING THE THIRD DIMENSION IN CONTRASTIVE LEARNING, [Paper]

• (arXiv 2023.1) Understanding Self-Supervised Pretraining with Part-Aware Representation Learning, [Paper]

• (arXiv 2023.1) Hypergraph Transformer for Skeleton-based Action Recognition, [Paper]

• (arXiv 2023.1) CPT-V: A Contrastive Approach to Post-Training Quantization of Vision Transformers, [Paper]

• (arXiv 2023.1) InstructPix2Pix: Learning to Follow Image Editing Instructions, [Paper], [Code]

• (arXiv 2023.1) OvarNet: Towards Open-vocabulary Object Attribute Recognition, [Paper], [Project]

• (arXiv 2023.1) DDS: Decoupled Dynamic Scene-Graph Generation Network, [Paper]

• (arXiv 2023.1) Token Transformer: Can class token help window-based transformer build better long-range interactions? [Paper]

• (arXiv 2023.1) Toward Building General Foundation Models for Language, Vision, and Vision-Language Understanding Tasks, [Paper]

• (arXiv 2023.1) Multimodal Inverse Cloze Task for Knowledge-based Visual Question Answering? [Paper], [Code]

• (arXiv 2023.1) FGAHOI: Fine-Grained Anchors for Human-Object Interaction Detection, [Paper], [Code]

• (arXiv 2023.1) Parallel Reasoning Network for Human-Object Interaction Detection, [Paper]

• (arXiv 2023.1) In Defense of Structural Symbolic Representation for Video Event-Relation Prediction, [Paper]

• (arXiv 2023.1) Scene Synthesis from Human Motion, [Paper], [Project]

2022.12

• (arXiv 2022.12) EVA: Exploring the Limits of Masked Visual Representation Learning at Scale, [Paper], [Code]

• (arXiv 2022.12) OneFormer: One Transformer to Rule Universal Image Segmentation, [Paper], [Code]

• (arXiv 2022.12) MMDialog: A Large-scale Multi-turn Dialogue Dataset Towards Multi-modal Open-domain Conversation, [Paper], [Project]

• (arXiv 2022.12) Why is Winoground Hard? Investigating Failures in Visuolinguistic Compositionality, [Paper], [Code]

• (arXiv 2022.12) Multimodal Information Bottleneck: Learning Minimal Sufficient Unimodal and Multimodal Representations, [Paper], [Code]

• (arXiv 2022.12) CLIP-FLOW: CONTRASTIVE LEARNING BY SEMISUPERVISED ITERATIVE PSEUDO LABELING FOR OPTICAL FLOW ESTIMATION, [Paper]

• (arXiv 2022.12) INSTRUCTION-FOLLOWING AGENTS WITH JOINTLY PRE-TRAINED VISION-LANGUAGE MODELS, [Paper], [Code]

• (arXiv 2022.12) MetaFormer Baselines for Vision, [Paper], [Code]

• (arXiv 2022.12) ViTCoD: Vision Transformer Acceleration via Dedicated Algorithm and Accelerator Co-Design, [Paper], [Code]

• (arXiv 2022.12) FROM PLAY TO POLICY: CONDITIONAL BEHAVIOR GENERATION FROM UNCURATED ROBOT DATA, [Paper], [Project]

• (arXiv 2022.12) Optimizing Prompts for Text-to-Image Generation, [Paper], [Code]

• (arXiv 2022.12) Attentive Mask CLIP, [Paper]

• (arXiv 2022.12) Rethinking Cooking State Recognition with Vision Transformers, [Paper]

• (arXiv 2022.12) Enhancing Multi-modal and Multi-hop Question Answering via Structured Knowledge and Unified Retrieval-Generation, [Paper], [Code]

• (arXiv 2022.12) MM-SHAP: A Performance-agnostic Metric for Measuring Multimodal Contributions in Vision and Language Models & Tasks, [Paper], [Code]

• (arXiv 2022.12) RepQ-ViT: Scale Reparameterization for Post-Training Quantization of Vision Transformers, [Paper]

• (arXiv 2022.12) WAVENHANCER: UNIFYING WAVELET AND TRANSFORMER FOR IMAGE ENHANCEMENT, [Paper]

• (arXiv 2022.12) AUTOENCODERS AS CROSS-MODAL TEACHERS: CAN PRETRAINED 2D IMAGE TRANSFORMERS HELP 3D REPRESENTATION LEARNING?, [Paper], [Code]

• (arXiv 2022.12) SceneGATE: Scene-Graph based co-Attention networks for TExt visual question answering, [Paper]

• (arXiv 2022.12) Emergent Analogical Reasoning in Large Language Models, [Paper]

• (arXiv 2022.12) Unleashing the Power of Visual Prompting At the Pixel Level, [Paper], [Code]

• (arXiv 2022.12) Does CLIP Bind Concepts? Probing Compositionality in Large Image Models, [Paper]

• (arXiv 2022.12) LayoutDETR: Detection Transformer Is a Good Multimodal Layout Designer, [Paper], [Code]

• (arXiv 2022.12) Towards Unsupervised Visual Reasoning: Do Off-The-Shelf Features Know How to Reason?, [Paper]

• (arXiv 2022.12) Benchmarking Spatial Relationships in Text-to-Image Generation, [Paper], [Project]

• (arXiv 2022.12) MetaCLUE: Towards Comprehensive Visual Metaphors Research, [Paper], [Project]

• (arXiv 2022.12) Tackling Ambiguity with Images: Improved Multimodal Machine Translation and Contrastive Evaluation, [Paper], [Code]

• (arXiv 2022.12) Cross-modal Attention Congruence Regularization for Vision-Language Relation Alignment, [Paper]

• (arXiv 2022.12) Does unsupervised grammar induction need pixels?, [Paper]

• (arXiv 2022.12) Hi-LASSIE: High-Fidelity Articulated Shape and Skeleton Discovery from Sparse Image Ensemble, [Paper]

• (arXiv 2022.12) MAViC: Multimodal Active Learning for Video Captioning, [Paper]

• (arXiv 2022.12) What Makes for Good Tokenizers in Vision Transformer? [Paper]

• (arXiv 2022.12) Not Just Pretty Pictures: Text-to-Image Generators Enable Interpretable Interventions for Robust Representations, [Paper], [Code]

• (arXiv 2022.12) Generalized Decoding for Pixel, Image, and Language, [Paper], [Project]

• (arXiv 2022.12) METEOR Guided Divergence for Video Captioning, [Paper], [Code]

• (arXiv 2022.12) SLGTFORMER: AN ATTENTION-BASED APPROACH TO SIGN LANGUAGE RECOGNITION, [Paper], [Code]

• (arXiv 2022.12) FROM IMAGES TO TEXTUAL PROMPTS: ZERO-SHOT VQA WITH FROZEN LARGE LANGUAGE MODELS, [Paper], [Code]

• (arXiv 2022.12) 3D Highlighter: Localizing Regions on 3D Shapes via Text Descriptions, [Paper], [Code]

• (arXiv 2022.12) Contrastive Language-Vision AI Models Pretrained on Web-Scraped Multimodal Data Exhibit Sexual Objectification Bias, [Paper]

• (arXiv 2022.12) Ultra-High-Definition Low-Light Image Enhancement: A Benchmark and Transformer-Based Method, [Paper], [Code]

• (arXiv 2022.12) Tune-A-Video: One-Shot Tuning of Image Diffusion Models for Text-to-Video Generation, [Paper], [Project]

• (arXiv 2022.12) Beyond SOT: It’s Time to Track Multiple Generic Objects at Once, [Paper]

• (arXiv 2022.12) KNOWLEDGE-DRIVEN SCENE PRIORS FOR SEMANTIC AUDIO-VISUAL EMBODIED NAVIGATION, [Paper]

• (arXiv 2022.12) SegViT: Semantic Segmentation with Plain Vision Transformers, [Paper], [Code]

• (arXiv 2022.12) Open-Vocabulary Temporal Action Detection with Off-the-Shelf Image-Text Features, [Paper]

• (arXiv 2022.12) Point·E: A System for Generating 3D Point Clouds from Complex Prompts, [Paper], [Code]

• (arXiv 2022.12) Inductive Attention for Video Action Anticipation, [Paper]

• (arXiv 2022.12) Image-and-Language Understanding from Pixels Only, [Paper], [Code]

• (arXiv 2022.12) FlexiViT: One Model for All Patch Sizes, [Paper], [Code]

• (arXiv 2022.12) Unsupervised Object Localization: Observing the Background to Discover Objects, [Paper], [Code]

• (arXiv 2022.12) Vision Transformers are Parameter-Efficient Audio-Visual Learners, [Paper], [Project]

• (arXiv 2022.12) Full Contextual Attention for Multi-resolution Transformers in Semantic Segmentation, [Paper]

• (arXiv 2022.12) DETR4D: Direct Multi-View 3D Object Detection with Sparse Attention, [Paper]

• (arXiv 2022.12) Enhanced Training of Query-Based Object Detection via Selective Query Recollection, [Paper], [Code]

• (arXiv 2022.12) TEXT-GUIDED MASK-FREE LOCAL IMAGE RETOUCHING, [Paper]

• (arXiv 2022.12) Summary-Oriented Vision Modeling for Multimodal Abstractive Summarization, [Paper], [Code]

• (arXiv 2022.12) One-Shot Domain Adaptive and Generalizable Semantic Segmentation with Class-Aware Cross-Domain Transformers, [Paper]

• (arXiv 2022.12) ConQueR: Query Contrast Voxel-DETR for 3D Object Detection, [Paper]

• (arXiv 2022.12) Examining the Difference Among Transformers and CNNs with Explanation Methods, [Paper]

• (arXiv 2022.12) Find Someone Who: Visual Commonsense Understanding in Human-Centric Grounding, [Paper], [Code]

• (arXiv 2022.12) Dual-branch Cross-Patch Attention Learning for Group Affect Recognition, [Paper]

• (arXiv 2022.12) Cross-Modal Similarity-Based Curriculum Learning for Image Captioning, [Paper]

• (arXiv 2022.12) NLIP: Noise-robust Language-Image Pre-training, [Paper]

• (arXiv 2022.12) LidarCLIP or: How I Learned to Talk to Point Clouds, [Paper], [Code]

• (arXiv 2022.12) CLIPSEP: LEARNING TEXT-QUERIED SOUND SEPARATION WITH NOISY UNLABELED VIDEOS, [Paper]

• (arXiv 2022.12) Reproducible scaling laws for contrastive language-image learning, [Paper], [Code]

• (arXiv 2022.12) WHAT DO VISION TRANSFORMERS LEARN? A VISUAL EXPLORATION, [Paper]

• (arXiv 2022.12) Self-Play and Self-Describe: Policy Adaptation with Vision-Language Foundation Models, [Paper], [Project]

• (arXiv 2022.12) GPVIT: A HIGH RESOLUTION NON-HIERARCHICAL VISION TRANSFORMER WITH GROUP PROPAGATION, [Paper], [Code]

• (arXiv 2022.12) Learning 3D Representations from 2D Pre-trained Models via Image-to-Point Masked Autoencoders, [Paper], [Code]

• (arXiv 2022.12) Parallel Queries for Human-Object Interaction Detection, [Paper]

• (arXiv 2022.12) Structure-Guided Image Completion with Image-level and Object-level Semantic Discriminators, [Paper]

• (arXiv 2022.12) Localized Latent Updates for Fine-Tuning Vision-Language Models, [Paper]

• (arXiv 2022.12) CamoFormer: Masked Separable Attention for Camouflaged Object Detection, [Paper]

• (arXiv 2022.12) FastMIM: Expediting Masked Image Modeling Pre-training for Vision, [Paper], [Code]

• (arXiv 2022.12) OAMixer: Object-aware Mixing Layer for Vision Transformers, [Paper], [Code]

• (arXiv 2022.12) Doubly Right Object Recognition: A Why Prompt for Visual Rationales, [Paper]

• (arXiv 2022.12) RT-1: ROBOTICS TRANSFORMER FOR REAL-WORLD CONTROL AT SCALE, [Paper], [Project]

• (arXiv 2022.12) Egocentric Video Task Translation, [Paper]

• (arXiv 2022.12) ScanEnts3D: Exploiting Phrase-to-3D-Object Correspondences for Improved Visio-Linguistic Models in 3D Scenes, [Paper], [Project]

• (arXiv 2022.12) Curriculum Learning Meets Weakly Supervised Modality Correlation Learning, [Paper]

• (arXiv 2022.12) IMoS: Intent-Driven Full-Body Motion Synthesis for Human-Object Interactions, [Paper]

• (arXiv 2022.12) MultiAct: Long-Term 3D Human Motion Generation from Multiple Action Labels, [Paper]

• (arXiv 2022.12) A New Path: Scaling Vision-and-Language Navigation with Synthetic Instructions and Imitation Learning, [Paper]

• (arXiv 2022.12) Beyond Object Recognition: A New Benchmark towards Object Concept Learning, [Paper], [Project]

• (arXiv 2022.12) ViTPose+: Vision Transformer Foundation Model for Generic Body Pose Estimation, [Paper], [Code]

• (arXiv 2022.12) Structured Vision-Language Pretraining for Computational Cooking, [Paper]

• (arXiv 2022.12) MIME: Human-Aware 3D Scene Generation, [Paper], [Project]

• (arXiv 2022.12) OFASY S: A Multi-Modal Multi-Task Learning System for Building Generalist Models, [Paper], [Code]

• (arXiv 2022.12) Task Bias in Vision-Language Models, [Paper]

• (arXiv 2022.12) Multi-Concept Customization of Text-to-Image Diffusion, [Paper], [Code]

• (arXiv 2022.12) Few-View Object Reconstruction with Unknown Categories and Camera Poses, [Paper], [Project]

• (arXiv 2022.12) Masked Video Distillation: Rethinking Masked Feature Modeling for Self-supervised Video Representation Learning, [Paper], [Code]

• (arXiv 2022.12) Learning Video Representations from Large Language Models, [Paper], [Project]

• (arXiv 2022.12) Frozen CLIP Model is Efficient Point Cloud Backbone, [Paper]

• (arXiv 2022.12) DialogCC: Large-scale Multi-Modal Dialogue Dataset, [Paper], [Project]

• (arXiv 2022.12) Group Generalized Mean Pooling for Vision Transformer, [Paper]

• (arXiv 2022.12) LEARNING DOMAIN INVARIANT PROMPT FOR VISION-LANGUAGE MODELS, [Paper]

• (arXiv 2022.12) LLM-Planner: Few-Shot Grounded Planning for Embodied Agents with Large Language Models, [Paper]

• (arXiv 2022.12) Hyperbolic Contrastive Learning for Visual Representations beyond Objects, [Paper], [Code]

2022.11

• (arXiv 2022.11) Texts as Images in Prompt Tuning for Multi-Label Image Recognition, [Paper], [Code]

• (arXiv 2022.11) Tell Me What Happened: Unifying Text-guided Video Completion via Multimodal Masked Video Generation, [Paper]

• (arXiv 2022.11) InDiReCT: Language-Guided Zero-Shot Deep Metric Learning for Images, [Paper]

• (arXiv 2022.11) VoP: Text-Video Co-operative Prompt Tuning for Cross-Modal Retrieval, [Paper], [Code]

• (arXiv 2022.11) Completing point cloud from few points by Wasserstein GAN and Transformers, [Paper], [Code]

• (arXiv 2022.11) Integrally Pre-Trained Transformer Pyramid Networks, [Paper], [Code]

• (arXiv 2022.11) Data Augmentation Vision Transformer for Fine-grained Image Classification, [Paper]

• (arXiv 2022.11) DETRs with Collaborative Hybrid Assignments Training, [Paper], [Code]

• (arXiv 2022.11) Open-vocabulary Attribute Detection, [Paper], [Project]

• (arXiv 2022.11) Lite-Mono: A Lightweight CNN and Transformer Architecture for Self-Supervised Monocular Depth Estimation, [Paper], [Code]

• (arXiv 2022.11) Inversion-Based Creativity Transfer with Diffusion Models, [Paper], [Code]

• (arXiv 2022.11) CODA-Prompt: COntinual Decomposed Attention-based Prompting for Rehearsal-Free Continual Learning, [Paper]

• (arXiv 2022.11) SVFormer: Semi-supervised Video Transformer for Action Recognition, [Paper], [Code]

• (arXiv 2022.11) Generalizable Implicit Neural Representations via Instance Pattern Composers, [Paper]

• (arXiv 2022.11) Improving Visual-textual Sentiment Analysis by Fusing Expert Features, [Paper]

• (arXiv 2022.11) Self-Supervised Learning based on Heat Equation, [Paper]

• (arXiv 2022.11) Peekaboo: Text to Image Diffusion Models are Zero-Shot Segmentors, [Paper]

• (arXiv 2022.11) Paint by Example: Exemplar-based Image Editing with Diffusion Models, [Paper], [Code]

• (arXiv 2022.11) Human or Machine? Turing Tests for Vision and Language, [Paper], [Code]

• (arXiv 2022.11) Teach-DETR: Better Training DETR with Teachers, [Paper], [Code]

• (arXiv 2022.11) Conv2Former: A Simple Transformer-Style ConvNet for Visual Recognition, [Paper]

• (arXiv 2022.11) X^2-VLM: All-In-One Pre-trained Model For Vision-Language Tasks, [Paper], [Code]

• (arXiv 2022.11) Aligning Source Visual and Target Language Domains for Unpaired Video Captioning, [Paper]

• (arXiv 2022.11) On the Transferability of Visual Features in Generalized Zero-Shot Learning, [Paper], [Code]

• (arXiv 2022.11) Generalizable Industrial Visual Anomaly Detection with Self-Induction Vision Transformer, [Paper]

• (arXiv 2022.11) Transformer Based Multi-Grained Features for Unsupervised Person Re-Identification, [Paper], [Code]

• (arXiv 2022.11) Efficient Frequency Domain-based Transformers for High-Quality Image Deblurring, [Paper], [Code]

• (arXiv 2022.11) Event Transformer+. A multi-purpose solution for efficient event data processing, [Paper]

• (arXiv 2022.11) MagicPony: Learning Articulated 3D Animals in the Wild, [Paper], [Project]

• (arXiv 2022.11) Gated Class-Attention with Cascaded Feature Drift Compensation for Exemplar-free Continual Learning of Vision Transformers, [Paper], [Code]

• (arXiv 2022.11) Expectation-Maximization Contrastive Learning for Compact Video-and-Language Representations, [Paper], [Code]

• (arXiv 2022.11) N-Gram in Swin Transformers for Efficient Lightweight Image Super-Resolution, [Paper]

• (arXiv 2022.11) Robotic Skill Acquisition via Instruction Augmentation with Vision-Language Models, [Paper], [Code]

• (arXiv 2022.11) Peeling the Onion: Hierarchical Reduction of Data Redundancy for Efficient Vision Transformer Training, [Paper], [Code]

• (arXiv 2022.11) Unifying Vision-Language Representation Space with Single-tower Transformer, [Paper]

• (arXiv 2022.11) DeepSolo: Let Transformer Decoder with Explicit Points Solo for Text Spotting, [Paper]

• (arXiv 2022.11) Castling-ViT: Compressing Self-Attention via Switching Towards Linear-Angular Attention During Vision Transformer Inference, [Paper]

• (arXiv 2022.11) CL-CrossVQA: A Continual Learning Benchmark for Cross-Domain Visual Question Answering, [Paper]

• (arXiv 2022.11) Normal Transformer: Extracting Surface Geometry from LiDAR Points Enhanced by Visual Semantics, [Paper]

• (arXiv 2022.11) A Unified Model for Video Understanding and Knowledge Embedding with Heterogeneous Knowledge Graph Dataset, [Paper]

• (arXiv 2022.11) Efficient Video Representation Learning via Masked Video Modeling with Motion-centric Token Selection, [Paper]

• (arXiv 2022.11) DiffStyler: Controllable Dual Diffusion for Text-Driven Image Stylization, [Paper]

• (arXiv 2022.11) TORE: Token Reduction for Efficient Human Mesh Recovery with Transformer, [Paper]

• (arXiv 2022.11) Synthesizing Coherent Story with Auto-Regressive Latent Diffusion Models, [Paper], [Code]

• (arXiv 2022.11) Are Out-of-Distribution Detection Methods Reliable?, [Paper]

• (arXiv 2022.11) GLT-T: Global-Local Transformer Voting for 3D Single Object Tracking in Point Clouds, [Paper], [Code]

• (arXiv 2022.11) CROSS-MODAL CONTRASTIVE LEARNING FOR ROBUST REASONING IN VQA, [Paper], [Code]

• (arXiv 2022.11) LISA: Localized Image Stylization with Audio via Implicit Neural Representation, [Paper]

• (arXiv 2022.11) MagicVideo: Efficient Video Generation With Latent Diffusion Models, [Paper], [Code]

• (arXiv 2022.11) DreamArtist: Towards Controllable One-Shot Text-to-Image Generation via Contrastive Prompt-Tuning, [Paper]

• (arXiv 2022.11) Hybrid Transformer Based Feature Fusion for Self-Supervised Monocular Depth Estimation, [Paper]

• (arXiv 2022.11) Language in a Bottle: Language Model Guided Concept Bottlenecks for Interpretable Image Classification, [Paper]

• (arXiv 2022.11) Structure-Encoding Auxiliary Tasks for Improved Visual Representation in Vision-and-Language Navigation, [Paper]

• (arXiv 2022.11) You Need Multiple Exiting: Dynamic Early Exiting for Accelerating Unified Vision Language Model, [Paper]

• (arXiv 2022.11) Beyond Attentive Tokens: Incorporating Token Importance and Diversity for Efficient Vision Transformers, [Paper]

• (arXiv 2022.11) FlowLens: Seeing Beyond the FoV via Flow-guided Clip-Recurrent Transformer, [Paper], [Code]

• (arXiv 2022.11) PS-Transformer: Learning Sparse Photometric Stereo Network using Self-Attention Mechanism, [Paper]

• (arXiv 2022.11) On the Robustness, Generalization, and Forgetting of Shape-Texture Debiased Continual Learning, [Paper]

• (arXiv 2022.11) Vision Transformer with Super Token Sampling, [Paper], [Code]

• (arXiv 2022.11) Detect Only What You Specify : Object Detection with Linguistic Target, [Paper]

• (arXiv 2022.11) Visual Programming: Compositional visual reasoning without training, [Paper], [Project]

• (arXiv 2022.11) ClipCrop: Conditioned Cropping Driven by Vision-Language Model, [Paper]

• (arXiv 2022.11) SMAUG: Sparse Masked Autoencoder for Efficient Video-Language Pre-training, [Paper]

• (arXiv 2022.11) Blur Interpolation Transformer for Real-World Motion from Blur, [Paper]

• (arXiv 2022.11) Mean Shift Mask Transformer for Unseen Object Instance Segmentation, [Paper], [Code]

• (arXiv 2022.11) PointCLIP V2: Adapting CLIP for Powerful 3D Open-world Learning, [Paper], [Code]

• (arXiv 2022.11) Exploring Discrete Diffusion Models for Image Captioning, [Paper], [Code]

• (arXiv 2022.11) PERCEIVER-VL: Efficient Vision-and-Language Modeling with Iterative Latent Attention, [Paper], [Code]

• (arXiv 2022.11) Multitask Vision-Language Prompt Tuning, [Paper], [Code]

• (arXiv 2022.11) Teaching Structured Vision & Language Concepts to Vision & Language Models, [Paper]

• (arXiv 2022.11) WEIGHTED ENSEMBLE SELF-SUPERVISED LEARNING, [Paper]

• (arXiv 2022.11) BEVFormer v2: Adapting Modern Image Backbones to Bird’s-Eye-View Recognition via Perspective Supervision, [Paper]

• (arXiv 2022.11) Task Residual for Tuning Vision-Language Models, [Paper], [Code]

• (arXiv 2022.11) α DARTS Once More: Enhancing Differentiable Architecture Search by Masked Image Modeling, [Paper]

• (arXiv 2022.11) Delving into Transformer for Incremental Semantic Segmentation, [Paper]

• (arXiv 2022.11) DETRDistill: A Universal Knowledge Distillation Framework for DETR-families, [Paper]

• (arXiv 2022.11) PromptCap: Prompt-Guided Task-Aware Image Captioning, [Paper]

• (arXiv 2022.11) UNIFORMERV2: SPATIOTEMPORAL LEARNING BY ARMING IMAGE VITS WITH VIDEO UNIFORMER, [Paper], [Code]

• (arXiv 2022.11) Masked Reconstruction Contrastive Learning with Information Bottleneck Principle, [Paper]

• (arXiv 2022.11) Listen, denoise, action! Audio-driven motion synthesis with diffusion models, [Paper], [Project]

• (arXiv 2022.11) ConStruct-VL: Data-Free Continual Structured VL Concepts Learning, [Paper]

• (arXiv 2022.11) How to Fine-Tune Vision Models with SGD, [Paper]

• (arXiv 2022.11) Progressive Tree-Structured Prototype Network for End-to-End Image Captioning, [Paper], [Code]

• (arXiv 2022.11) CapEnrich: Enriching Caption Semantics for Web Images via Cross-modal Pre-trained Knowledge, [Paper], [Code]

• (arXiv 2022.11) Visual Commonsense-aware Representation Network for Video Captioning, [Paper], [Code]

• (arXiv 2022.11) Language Conditioned Spatial Relation Reasoning for 3D Object Grounding, [Paper], [Code]

• (arXiv 2022.11) HARDVS: Revisiting Human Activity Recognition with Dynamic Vision Sensors, [Paper], [Code]

• (arXiv 2022.11) Towards All-in-one Pre-training via Maximizing Multi-modal Mutual Information, [Paper], [Code]

• (arXiv 2022.11) Uni-Perceiver v2: A Generalist Model for Large-Scale Vision and Vision-Language Tasks, [Paper], [Code]

• (arXiv 2022.11) D^3ETR: Decoder Distillation for Detection Transformer, [Paper]

• (arXiv 2022.11) CAE v2: Context Autoencoder with CLIP Target, [Paper]

• (arXiv 2022.11) Cross-Modal Adapter for Text-Video Retrieval, [Paper], [Code]

• (arXiv 2022.11) TOKEN TURING MACHINES, [Paper]

• (arXiv 2022.11) WILL LARGE-SCALE GENERATIVE MODELS CORRUPT FUTURE DATASETS? [Paper], [Code]

• (arXiv 2022.11) Demystify Self-Attention in Vision Transformers from a Semantic Perspective: Analysis and Application, [Paper]

• (arXiv 2022.11) SATVSR: Scenario Adaptive Transformer for Cross Scenarios Video Super-Resolution, [Paper]

• (arXiv 2022.11) TransCC: Transformer-based Multiple Illuminant Color Constancy Using Multitask Learning, [Paper]

• (arXiv 2022.11) Stare at What You See: Masked Image Modeling without Reconstruction, [Paper], [Code]

• (arXiv 2022.11) HeatViT: Hardware-Efficient Adaptive Token Pruning for Vision Transformers, [Paper]

• (arXiv 2022.11) Cross-domain Federated Adaptive Prompt Tuning for CLIP, [Paper]

• (arXiv 2022.11) YORO - Lightweight End to End Visual Grounding, [Paper]

• (arXiv 2022.11) Knowledge Distillation for Detection Transformer with Consistent Distillation Points Sampling, [Paper]

• (arXiv 2022.11) BiViT: Extremely Compressed Binary Vision Transformer, [Paper]

• (arXiv 2022.11) ContextCLIP: Contextual Alignment of Image-Text pairs on CLIP visual representations, [Paper]

• (arXiv 2022.11) Zero-shot Image Captioning by Anchor-augmented Vision-Language Space Alignment, [Paper]

• (arXiv 2022.11) Seeing Beyond the Brain: Conditional Diffusion Model with Sparse Masked Modeling for Vision Decoding, [Paper], [Project]

• (arXiv 2022.11) Enhancing Few-Shot Image Classification with Cosine Transformer, [Paper], [Code]

• (arXiv 2022.11) SCOTCH and SODA: A Transformer Video Shadow Detection Framework, [Paper]

• (arXiv 2022.11) AU-Aware Vision Transformers for Biased Facial Expression Recognition, [Paper]

• (arXiv 2022.11) Fast Text-Conditional Discrete Denoising on Vector-Quantized Latent Spaces, [Paper], [Code]

• (arXiv 2022.11) Large-Scale Bidirectional Training for Zero-Shot Image Captioning, [Paper]

• (arXiv 2022.11) Grafting Pre-trained Models for Multimodal Headline Generation, [Paper]

• (arXiv 2022.11) CabViT: Cross Attention among Blocks for Vision Transformer, [Paper], [Code]

• (arXiv 2022.11) Composed Image Retrieval with Text Feedback via Multi-grained Uncertainty Regularization, [Paper]

• (arXiv 2022.11) SSGVS: Semantic Scene Graph-to-Video Synthesis, [Paper]

• (arXiv 2022.11) One-Time Model Adaptation to Heterogeneous Clients: An Intra-Client and Inter-Image Attention Design, [Paper]

• (arXiv 2022.11) An Improved End-to-End Multi-Target Tracking Method Based on Transformer Self-Attention, [Paper]

• (arXiv 2022.11) Zero-shot Visual Commonsense Immorality Prediction, [Paper], [Code]

• (arXiv 2022.11) Hyperbolic Cosine Transformer for LiDAR 3D Object Detection, [Paper]

• (arXiv 2022.11) Training a Vision Transformer from scratch in less than 24 hours with 1 GPU, [Paper], [Code]

• (arXiv 2022.11) ViTALiTy: Unifying Low-rank and Sparse Approximation for Vision Transformer Acceleration with a Linear Taylor Attention, [Paper]

• (arXiv 2022.11) SimOn: A Simple Framework for Online Temporal Action Localization, [Paper], [Code]

• (arXiv 2022.11) ERNIE-UNIX^2: A UNIFIED CROSS-LINGUAL CROSS-MODAL FRAMEWORK FOR UNDERSTANDING AND GENERATION, [Paper]

• (arXiv 2022.11) SG-Shuffle: Multi-aspect Shuffle Transformer for Scene Graph Generation, [Paper]

• (arXiv 2022.11) Understanding Cross-modal Interactions in V&L Models that Generate Scene Descriptions, [Paper]

• (arXiv 2022.11) VieCap4H - VLSP 2021: ObjectAoA - Enhancing performance of Object Relation Transformer with Attention on Attention for Vietnamese image captioning, [Paper]

• (arXiv 2022.11) Watching the News: Towards VideoQA Models that can Read, [Paper], [Project]

• (arXiv 2022.11) Efficient Joint Detection and Multiple Object Tracking with Spatially Aware Transformer, [Paper]

• (arXiv 2022.11) Demystify Transformers & Convolutions in Modern Image Deep Networks, [Paper], [Code]

• (arXiv 2022.11) InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions, [Paper], [Code]

• (arXiv 2022.11) DEPTHFORMER: MULTIMODAL POSITIONAL ENCODINGS AND CROSS-INPUT ATTENTION FOR TRANSFORMER-BASED SEGMENTATION NETWORKS, [Paper]

• (arXiv 2022.11) Sequential Transformer for End-to-End Person Search, [Paper]

• (arXiv 2022.11) Prompting Large Pre-trained Vision-Language Models For Compositional Concept Learning, [Paper]

• (arXiv 2022.11) CASA: Category-agnostic Skeletal Animal Reconstruction, [Paper]

• (arXiv 2022.11) ViT-CX: Causal Explanation of Vision Transformers, [Paper]

• (arXiv 2022.11) Disentangling Content and Motion for Text-Based Neural Video Manipulation, [Paper]

• (arXiv 2022.11) Efficient Multi-order Gated Aggregation Network, [Paper]

• (arXiv 2022.11) CLOP: Video-and-Language Pre-Training with Knowledge Regularizations, [Paper]

• (arXiv 2022.11) MSMG-Net: Multi-scale Multi-grained Supervised Metworks for Multi-task Image Manipulation Detection and Localization, [Paper]

• (arXiv 2022.11) Understanding and Mitigating Overfitting in Prompt Tuning for Vision-Language Models, [Paper], [Code]

• (arXiv 2022.11) Zero-shot Video Moment Retrieval With Off-the-Shelf Models, [Paper]

• (arXiv 2022.11) Scaling Multimodal Pre-Training via Cross-Modality Gradient Harmonization, [Paper]

• (arXiv 2022.11) A Transformer Architecture for Online Gesture Recognition of Mathematical Expressions, [Paper]

• (arXiv 2022.11) Evaluating and Improving Factuality in Multimodal Abstractive Summarization, [Paper], [Code]

• (arXiv 2022.11) RCDPT: RADAR-CAMERA FUSION DENSE PREDICTION TRANSFORMER, [Paper]

• (arXiv 2022.11) Video Event Extraction via Tracking Visual States of Arguments, [Paper]

• (arXiv 2022.11) The Lottery Ticket Hypothesis for Vision Transformers, [Paper]

• (arXiv 2022.11) TEXTCRAFT: ZERO-SHOT GENERATION OF HIGHFIDELITY AND DIVERSE SHAPES FROM TEXT, [Paper]

• (arXiv 2022.11) PolyBuilding: Polygon Transformer for End-to-End Building Extraction, [Paper]

• (arXiv 2022.11) RETHINKING HIERARCHIES IN PRE-TRAINED PLAIN VISION TRANSFORMER, [Paper], [Code]

• (arXiv 2022.11) SAP-DETR: Bridging the Gap Between Salient Points and Queries-Based Transformer Detector for Fast Model Convergency, [Paper]

• (arXiv 2022.11) Could Giant Pretrained Image Models Extract Universal Representations? [Paper]

• (arXiv 2022.11) MAEDAY: MAE for few and zero shot AnomalY-Detection, [Paper], [Code]

• (arXiv 2022.11) Degenerate Swin to Win: Plain Window-based Transformer without Sophisticated Operations, [Paper]

• (arXiv 2022.11) Look Around and Refer: 2D Synthetic Semantics Knowledge Distillation for 3D Visual Grounding, [Paper], [Code]

• (arXiv 2022.11) SpaText: Spatio-Textual Representation for Controllable Image Generation, [Paper], [Project]

• (arXiv 2022.11) Learning 3D Scene Priors with 2D Supervision, [Paper], [Project]

• (arXiv 2022.11) PoET: Pose Estimation Transformer for Single-View, Multi-Object 6D Pose Estimation, [Paper], [Code]

• (arXiv 2022.11) Spatial-Spectral Transformer for Hyperspectral Image Denoising, [Paper], [Code]

• (arXiv 2022.11) Training Vision-Language Models with Less Bimodal Supervision, [Paper]

• (arXiv 2022.11) Text-Only Training for Image Captioning using Noise-Injected CLIP, [Paper], [Code]

• (arXiv 2022.11) Attention-based Neural Cellular Automata, [Paper]

• (arXiv 2022.11) eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers, [Paper], [Code]

• (arXiv 2022.11) Chinese CLIP: Contrastive Vision-Language Pretraining in Chinese, [Paper], [Code]

• (arXiv 2022.11) P^3OVD: Fine-grained Visual-Text Prompt-Driven Self-Training for Open-Vocabulary Object Detection, [Paper]

• (arXiv 2022.11) tSF: Transformer-based Semantic Filter for Few-Shot Learning, [Paper]

• (arXiv 2022.11) WITT: A WIRELESS IMAGE TRANSMISSION TRANSFORMER FOR SEMANTIC COMMUNICATIONS, [Paper], [Code]

• (arXiv 2022.11) Pair DETR: Contrastive Learning Speeds Up DETR Training, [Paper]

• (arXiv 2022.11) Interaction Visual Transformer for Egocentric Action Anticipation, [Paper]

• (arXiv 2022.11) UDE: A Unified Driving Engine for Human Motion Generation, [Paper], [Code]

• (arXiv 2022.11) Action-GPT: Leveraging Large-scale Language Models for Improved and Generalized Zero Shot Action Generation, [Paper], [Project]

• (arXiv 2022.11) Human or Machine? Turing Tests for Vision and Language, [Paper], [Code]

• (arXiv 2022.11) Knowledge Prompting for Few-shot Action Recognition, [Paper]

• (arXiv 2022.11) UPainting: Unified Text-to-Image Diffusion Generation with Cross-modal Guidance, [Paper], [Project]

• (arXiv 2022.11) LVP-M^3: Language-aware Visual Prompt for Multilingual Multimodal Machine Translation, [Paper]

• (arXiv 2022.11) PROCONTEXT: PROGRESSIVE CONTEXT TRANSFORMER FOR TRACKING, [Paper], [Code]

• (arXiv 2022.11) Video based Object 6D Pose Estimation using Transformers, [Paper], [Code]

• (arXiv 2022.11) S2WAT: Image Style Transfer via Hierarchical Vision Transformer using Strips Window Attention, [Paper], [Code]

• (arXiv 2022.11) Holistic Interaction Transformer Network for Action Detection, [Paper], [Code]

• (arXiv 2022.11) Learning and Retrieval from Prior Data for Skill-based Imitation Learning, [Paper], [Code]

• (arXiv 2022.11) SimpleClick: Interactive Image Segmentation with Simple Vision Transformers, [Paper], [Code]

• (arXiv 2022.11) TANGO: Text-driven Photorealistic and Robust 3D Stylization via Lighting Decomposition, [Paper], [Code]

• (arXiv 2022.11) CPL: Counterfactual Prompt Learning for Vision and Language Models, [Paper], [Code]

• (arXiv 2022.11) Plug-and-Play VQA: Zero-shot VQA by Conjoining Large Pretrained Models with Zero Training, [Paper]

• (arXiv 2022.11) Selective Query-guided Debiasing for Video Corpus Moment Retrieval, [Paper]

• (arXiv 2022.11) Scaling & Shifting Your Features: A New Baseline for Efficient Model Tuning, [Paper], [Code]

• (arXiv 2022.11) DENOISING MASKED AUTOENCODERS ARE CERTIFIABLE ROBUST VISION LEARNERS, [Paper], [Code]

• (arXiv 2022.11) Token-Label Alignment for Vision Transformers, [Paper], [Code]

• (arXiv 2022.11) CLIP-Fields: Weakly Supervised Semantic Fields for Robotic Memory, [Paper], [Code]

• (arXiv 2022.11) Multi-Scale Wavelet Transformer for Face Forgery Detection, [Paper]

• (arXiv 2022.11) CLIP-PAE: PROJECTION-AUGMENTATION EMBEDDING TO EXTRACT RELEVANT FEATURES FOR A DISENTANGLED, INTERPRETABLE, AND CONTROLLABLE TEXT-GUIDED IMAGE MANIPULATION, [Paper]

• (arXiv 2022.11) VISUAL PROMPT TUNING FOR TEST-TIME DOMAIN ADAPTATION, [Paper]

• (arXiv 2022.11) FastCLIPstyler: Optimisation-free Text-based Image Style Transfer Using Style Representations, [Paper]

• (arXiv 2022.11) PROGRESSIVE DENOISING MODEL FOR FINEGRAINED TEXT-TO-IMAGE GENERATION, [Paper]

• (arXiv 2022.11) DALL-E-Bot: Introducing Web-Scale Diffusion Models to Robotics, [Paper], [Project]

• (arXiv 2022.11) Decomposed Soft Prompt Guided Fusion Enhancing for Compositional Zero-Shot Learning, [Paper], [Code]

• (arXiv 2022.11) ACCURATE IMAGE RESTORATION WITH ATTENTION RETRACTABLE TRANSFORMER, [Paper], [Code]

• (arXiv 2022.11) Dilated Neighborhood Attention Transformer, [Paper], [Code]

• (arXiv 2022.11) Unified Loss of Pair Similarity Optimization for Vision-Language Retrieval, [Paper]

• (arXiv 2022.11) TVLT: Textless Vision-Language Transformer, [Paper], [Code]

2022.10

• (arXiv 2022.10) DiMBERT: Learning Vision-Language Grounded Representations with Disentangled Multimodal-Attention, [Paper]

• (arXiv 2022.10) TFORMER: 3D TOOTH SEGMENTATION IN MESH SCANS WITH GEOMETRY GUIDED TRANSFORMER, [Paper]

• (arXiv 2022.10) ON-THE-FLY OBJECT DETECTION USING STYLEGAN WITH CLIP GUIDANCE, [Paper]

• (arXiv 2022.10) Image-free Domain Generalization via CLIP for 3D Hand Pose Estimation, [Paper]

• (arXiv 2022.10) Temporal-Viewpoint Transportation Plan for Skeletal Few-shot Action Recognition, [Paper]

• (arXiv 2022.10) A SIMPLE, EFFICIENT AND SCALABLE CONTRASTIVE MASKED AUTOENCODER FOR LEARNING VISUAL REPRESENTATIONS, [Paper]

• (arXiv 2022.10) Time-rEversed diffusioN tEnsor Transformer: A new TENET of Few-Shot Object Detection, [Paper]

• (arXiv 2022.10) Foreign Object Debris Detection for Airport Pavement Images based on Self-supervised Localization and Vision Transformer, [Paper]

• (arXiv 2022.10) ViT-LSLA: Vision Transformer with Light Self-Limited-Attention, [Paper]

• (arXiv 2022.10) Generative Negative Text Replay for Continual Vision-Language Pretraining, [Paper]

• (arXiv 2022.10) PatchRot: A Self-Supervised Technique for Training Vision Transformers, [Paper]

• (arXiv 2022.10) MULTIMODAL TRANSFORMER DISTILLATION FOR AUDIO-VISUAL SYNCHRONIZATION, [Paper]

• (arXiv 2022.10) Multimodal Transformer for Parallel Concatenated Variational Autoencoders, [Paper]

• (arXiv 2022.10) Differentially Private CutMix for Split Learning with Vision Transformer, [Paper]

• (arXiv 2022.10) OHMG: ZERO-SHOT OPEN-VOCABULARY HUMAN MOTION GENERATION, [Paper]

• (arXiv 2022.10) VLT: Vision-Language Transformer and Query Generation for Referring Segmentation, [Paper]

• (arXiv 2022.10) PSFORMER: POINT TRANSFORMER FOR 3D SALIENT OBJECT DETECTION, [Paper]

• (arXiv 2022.10) GRAFTING VISION TRANSFORMERS, [Paper]

• (arXiv 2022.10) Generalization Differences between End-to-End and Neuro-Symbolic Vision-Language Reasoning Systems, [Paper]

• (arXiv 2022.10) FaD-VLP: Fashion Vision-and-Language Pre-training towards Unified Retrieval and Captioning, [Paper]

• (arXiv 2022.10) Masked Vision-Language Transformer in Fashion, [Paper], [Code]

• (arXiv 2022.10) Learning Variational Motion Prior for Video-based Motion Capture, [Paper]

• (arXiv 2022.10) Open-vocabulary Semantic Segmentation with Frozen Vision-Language Models, [Paper], [Code]

• (arXiv 2022.10) TEXT2MODEL: MODEL INDUCTION FOR ZERO-SHOT GENERALIZATION USING TASK DESCRIPTIONS, [Paper]

• (arXiv 2022.10) Learning Joint Representation of Human Motion and Language, [Paper]

• (arXiv 2022.10) ERNIE-ViLG 2.0: Improving Text-to-Image Diffusion Model with Knowledge-Enhanced Mixture-of-Denoising-Experts, [Paper]

• (arXiv 2022.10) MSF3DDETR: Multi-Sensor Fusion 3D Detection Transformer for Autonomous Driving, [Paper]

• (arXiv 2022.10) Li3DeTr: A LiDAR based 3D Detection Transformer, [[Paper]](Li3DeTr: A LiDAR based 3D Detection Transformer)

• (arXiv 2022.10) Masked Transformer for image Anomaly Localization, [Paper]

• (arXiv 2022.10) Discovering Design Concepts for CAD Sketches, [Paper]

• (arXiv 2022.10) Compressing And Debiasing Vision-Language Pre-Trained Models for Visual Question Answering, [Paper]

• (arXiv 2022.10) End-to-End Multimodal Representation Learning for Video Dialog, [Paper]

• (arXiv 2022.10) TPFNet: A Novel Text In-painting Transformer for Text Removal, [Paper], [Code]

• (arXiv 2022.10) IMU2CLIP: MULTIMODAL CONTRASTIVE LEARNING FOR IMU MOTION SENSORS FROM EGOCENTRIC VIDEOS AND TEXT NARRATIONS, [Paper]

• (arXiv 2022.10) Can Transformer Attention Spread Give Insights Into Uncertainty of Detected and Tracked Objects? [Paper]

• (arXiv 2022.10) SemFormer: Semantic Guided Activation Transformer for Weakly Supervised Semantic Segmentation, [Paper], [Code]

• (arXiv 2022.10) End-to-end Tracking with a Multi-query Transformer, [Paper]

• (arXiv 2022.10) Explicitly Increasing Input Information Density for Vision Transformers on Small Datasets, [Paper], [Code]

• (arXiv 2022.10) TAMFORMER: MULTI-MODAL TRANSFORMER WITH LEARNED ATTENTION MASK FOR EARLY INTENT PREDICTION, [Paper]

• (arXiv 2022.10) VISUAL ANSWER LOCALIZATION WITH CROSS-MODAL MUTUAL KNOWLEDGE TRANSFER, [Paper], [Code]

• (arXiv 2022.10) Visual Semantic Parsing: From Images to Abstract Meaning Representation, [Paper]

• (arXiv 2022.10) End-to-end Transformer for Compressed Video Quality Enhancement, [Paper]

• (arXiv 2022.10) PlanT: Explainable Planning Transformers via Object-Level Representations, [Paper], [Project]

• (arXiv 2022.10) Strong-TransCenter: Improved Multi-Object Tracking based on Transformers with Dense Representations, [Paper], [Code]

• (arXiv 2022.10) GliTr: Glimpse Transformers with Spatiotemporal Consistency for Online Action Prediction, [Paper]

• (arXiv 2022.10) VLC-BERT: Visual Question Answering with Contextualized Commonsense Knowledge, [Paper], [Code]

• (arXiv 2022.10) Learning by Hallucinating: Vision-Language Pre-training with Weak Supervision, [Paper]

• (arXiv 2022.10) Learning Explicit Object-Centric Representations with Vision Transformers, [Paper]

• (arXiv 2022.10) Abductive Action Inference, [Paper]

• (arXiv 2022.10) Minutiae-Guided Fingerprint Embeddings via Vision Transformers, [Paper], [Code]

• (arXiv 2022.10) 3DALL-E: Integrating Text-to-Image AI in 3D Design Workflows, [Paper]

• (arXiv 2022.10) COMPOSING ENSEMBLES OF PRE-TRAINED MODELS VIA ITERATIVE CONSENSUS, [Paper], [Code]

• (arXiv 2022.10) Do Vision-and-Language Transformers Learn Grounded Predicate-Noun Dependencies?, [Paper]

• (arXiv 2022.10) Boosting vision transformers for image retrieval, [Paper], [Code]

• (arXiv 2022.10) LiteVL: Efficient Video-Language Learning with Enhanced Spatial-Temporal Modeling, [Paper]

• (arXiv 2022.10) Fine-grained Semantic Alignment Network for Weakly Supervised Temporal Language Grounding, [Paper]

• (arXiv 2022.10) Face Pyramid Vision Transformer, [Paper], [Code]

• (arXiv 2022.10) Context-Enhanced Stereo Transformer, [Paper], [Code]

• (arXiv 2022.10) CRT-6D: Fast 6D Object Pose Estimation with Cascaded Refinement Transformers, [Paper], [Code]

• (arXiv 2022.10) Rethinking Learning Approaches for Long-Term Action Anticipation, [Paper], [Code]

• (arXiv 2022.10) Extending Phrase Grounding with Pronouns in Visual Dialogues, [Paper], [Code]

• (arXiv 2022.10) Accumulated Trivial Attention Matters in Vision Transformers on Small Datasets, [Paper], [Code]

• (arXiv 2022.10) Transformers For Recognition In Overhead Imagery: A Reality Check, [Paper]

• (arXiv 2022.10) Anticipative Feature Fusion Transformer for Multi-Modal Action Anticipation, [Paper], [Code]

• (arXiv 2022.10) UIA-ViT: Unsupervised Inconsistency-Aware Method based on Vision Transformer for Face Forgery Detection, [Paper]

• (arXiv 2022.10) LCPFormer: Towards Effective 3D Point Cloud Analysis via Local Context Propagation in Transformers, [Paper]

• (arXiv 2022.10) Towards Real-Time Text2Video via CLIP-Guided, Pixel-Level Optimization, [Paper], [Code]

• (arXiv 2022.10) Language-free Training for Zero-shot Video Grounding, [Paper], [Code]

• (arXiv 2022.10) Foreground Guidance and Multi-Layer Feature Fusion for Unsupervised Object Discovery with Transformers, [Paper], [Code]

• (arXiv 2022.10) Towards Unifying Reference Expression Generation and Comprehension, [Paper]

• (arXiv 2022.10) Robust Self-Supervised Learning with Lie Groups, [Paper]

• (arXiv 2022.10) VIOLA: Imitation Learning for Vision-Based Manipulation with Object Proposal Priors, [Paper], [Code]

• (arXiv 2022.10) VTC: Improving Video-Text Retrieval with User Comments, [Paper], [Project]

• (arXiv 2022.10) SOLVING REASONING TASKS WITH A SLOT TRANSFORMER, [Paper], [Code]

• (arXiv 2022.10) Prompting through Prototype: A Prototype-based Prompt Learning on Pretrained Vision-Language Models, [Paper]

• (arXiv 2022.10) Grounded Video Situation Recognition, [Paper], [Project]

• (arXiv 2022.10) Single Image Super-Resolution Using Lightweight Networks Based on Swin Transformer, [Paper]

• (arXiv 2022.10) Visual Spatial Description: Controlled Spatial-Oriented Image-to-Text Generation, [Paper], [Code]

• (arXiv 2022.10) MovieCLIP: Visual Scene Recognition in Movies, [Paper]

• (arXiv 2022.10) PointTAD: Multi-Label Temporal Action Detection with Learnable Query Points, [Paper], [Code]

• (arXiv 2022.10) TOWARDS SUSTAINABLE SELF-SUPERVISED LEARNING, [Paper]

• (arXiv 2022.10) Visual-Semantic Contrastive Alignment for Few-Shot Image Classification, [Paper]

• (arXiv 2022.10) i-MAE: ARE LATENT REPRESENTATIONS IN MASKED AUTOENCODERS LINEARLY SEPARABLE? [Paper], [Code]

• (arXiv 2022.10) 2nd Place Solution to ECCV 2022 Challenge: Transformer-based Action recognition in hand-object interacting scenarios, [Paper]

• (arXiv 2022.10) 1st Place Solution to ECCV 2022 Challenge on HBHA: Transformer-based Global 3D Hand Pose Estimation in Two Hands Manipulating Objects Scenarios, [Paper]

• (arXiv 2022.10) DALLE-2 is Seeing Double: Flaws in Word-to-Concept Mapping in Text2Image Models, [Paper]

• (arXiv 2022.10) CLIP-Driven Fine-grained Text-Image Person Re-identification, [Paper]

• (arXiv 2022.10) Dense but Efficient VideoQA for Intricate Compositional Reasoning, [Paper]

• (arXiv 2022.10) Multi-view Gait Recognition based on SiameseVisionTransformer, [Paper]

• (arXiv 2022.10) TOIST: Task Oriented Instance Segmentation Transformer with Noun-Pronoun Distillation, [Paper], [Code]

• (arXiv 2022.10) CroCo: Self-Supervised Pre-training for 3D Vision Tasks by Cross-View Completion, [Paper], [Project]

• (arXiv 2022.10) A Unified View of Masked Image Modeling, [Paper], [Code]

• (arXiv 2022.10) Cross-Modal Fusion Distillation for Fine-Grained Sketch-Based Image Retrieval, [Paper], [Code]

• (arXiv 2022.10) BOAT: Bilateral Local Attention Vision Transformer, [Paper]

• (arXiv 2022.12) TOKEN MERGING: YOUR VIT BUT FASTER, [Paper], [Code]

• (arXiv 2022.10) Using Language to Extend to Unseen Domains, [Paper], [Code]

• (arXiv 2022.10) SWINV2-IMAGEN: HIERARCHICAL VISION TRANSFORMER DIFFUSION MODELS FOR TEXT-TO-IMAGE GENERATION, [Paper]

• (arXiv 2022.10) HUMANISE: Language-conditioned Human Motion Generation in 3D Scenes, [Paper], [Project]

• (arXiv 2022.10) Transfer-learning for video classification: Video Swin Transformer on multiple domains, [Paper]

• (arXiv 2022.10) PERCEPTUAL GROUPING IN VISION-LANGUAGE MODELS, [Paper]

• (arXiv 2022.10) How Mask Matters: Towards Theoretical Understandings of Masked Autoencoders, [Paper], [Code]

• (arXiv 2022.10) LINEAR VIDEO TRANSFORMER WITH FEATURE FIXATION, [Paper], [Code]

• (arXiv 2022.10) Transformer-based dimensionality reduction, [Paper]

• (arXiv 2022.10) Bridging the Domain Gap for Multi-Agent Perception, [Paper]

• (arXiv 2022.10) TransVisDrone: Spatio-Temporal Transformer for Vision-based Drone-to-Drone Detection in Aerial Videos, [Paper], [Code]

• (arXiv 2022.10) SCRATCHING VISUAL TRANSFORMER’S BACK WITH UNIFORM ATTENTION, [Paper]

• (arXiv 2022.10) Increasing Visual Awareness in Multimodal Neural Machine Translation from an Information Theoretic Perspective, [Paper]

• (arXiv 2022.10) TLDW: Extreme Multimodal Summarisation of News Videos, [Paper], [Code]

• (arXiv 2022.10) Character-Centric Story Visualization via Visual Planning and Token Alignment, [Paper], [Code]

• (arXiv 2022.10) COFAR: Commonsense and Factual Reasoning in Image Search, [Paper], [Code]

• (arXiv 2022.10) Learning Self-Regularized Adversarial Views for Self-Supervised Vision Transformers, [Paper], [Code]

• (arXiv 2022.10) Temporal and Contextual Transformer for Multi-Camera Editing of TV Shows, [Paper]

• (arXiv 2022.10) Forecasting Human Trajectory from Scene History, [Paper], [Code]

• (arXiv 2022.10) SGRAM: Improving Scene Graph Parsing via Abstract Meaning Representation, [Paper]

• (arXiv 2022.10) Contrastive Language-Image Pre-Training with Knowledge Graphs, [Paper]

• (arXiv 2022.10) A Saccaded Visual Transformer for General Object Spotting, [Paper]

• (arXiv 2022.10) Vision Transformers provably learn spatial structure, [Paper]

• (arXiv 2022.10) oViT: An Accurate Second-Order Pruning Framework for Vision Transformers, [Paper]

• (arXiv 2022.10) Fine-grained Category Discovery under Coarse-grained supervision with Hierarchical Weighted Self-contrastive Learning, [Paper], [Code]

• (arXiv 2022.10) Non-Contrastive Learning Meets Language-Image Pre-Training, [Paper]

• (arXiv 2022.10) Frame Mining: a Free Lunch for Learning Robotic Manipulation from 3D Point Clouds, [Paper], [Project]

• (arXiv 2022.10) Pretrained Transformers Do not Always Improve Robustness, [Paper]

• (arXiv 2022.10) Plausible May Not Be Faithful: Probing Object Hallucination in Vision-Language Pre-training, [Paper]

• (arXiv 2022.10) CONTRASTIVE AUDIO-VISUAL MASKED AUTOENCODER, [Paper]

• (arXiv 2022.10) SWFormer: Sparse Window Transformer for 3D Object Detection in Point Clouds, [Paper]

• (arXiv 2022.10) Trailers12k: Improving Transfer Learning with a Dual Image and Video Transformer for Multi-label Movie Trailer Genre Classification, [Paper]

• (arXiv 2022.10) AVLEN: Audio-Visual-Language Embodied Navigation in 3D Environments, [Paper]

• (arXiv 2022.10) MOVE: Unsupervised Movable Object Segmentation and Detection, [Paper]

• (arXiv 2022.10) IS SYNTHETIC DATA FROM GENERATIVE MODELS READY FOR IMAGE RECOGNITION?, [Paper], [Code]

• (arXiv 2022.10) Towards Transformer-based Homogenization of Satellite Imagery for Landsat-8 and Sentinel-2, [Paper]

• (arXiv 2022.10) MCTNET: A MULTI-SCALE CNN-TRANSFORMER NETWORK FOR CHANGE DETECTION IN OPTICAL REMOTE SENSING IMAGES, [Paper]

• (arXiv 2022.10) Vision Transformer Visualization: What Neurons Tell and How Neurons Behave? [Paper], [Code]

• (arXiv 2022.10) TokenMixup: Efficient Attention-guided Token-level Data Augmentation for Transformers, [Paper], [Code]

• (arXiv 2022.10) SQA3D: SITUATED QUESTION ANSWERING IN 3D SCENES, [Paper]

• (arXiv 2022.10) When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture, [Paper], [Code]

• (arXiv 2022.10) STAR-Transformer: A Spatio-temporal Cross Attention Transformer for Human Action Recognition, [Paper]

• (arXiv 2022.10) PedFormer: Pedestrian Behavior Prediction via Cross-Modal Attention Modulation and Gated Multitask Learning, [Paper]

• (arXiv 2022.10) One Model to Edit Them All: Free-Form Text-Driven Image Manipulation with Semantic Modulations, [Paper], [Code]

• (arXiv 2022.10) IMAGINARYNET: LEARNING OBJECT DETECTORS WITHOUT REAL IMAGES AND ANNOTATIONS, [Paper], [Code]

• (arXiv 2022.10) Feature-Proxy Transformer for Few-Shot Segmentation, [Paper], [Code]

• (arXiv 2022.10) Scene Text Image Super-Resolution via Content Perceptual Loss and Criss-Cross Transformer Blocks, [Paper]

• (arXiv 2022.10) UNIFIED VISION AND LANGUAGE PROMPT LEARNING, [Paper], [Code]

• (arXiv 2022.10) Exploring Long-Sequence Masked Autoencoders, [Paper], [Code]

• (arXiv 2022.10) MAPL: Parameter-Efficient Adaptation of Unimodal Pre-Trained Models for Vision-Language Few-Shot Prompting, [Paper]

• (arXiv 2022.10) Interactive Language: Talking to Robots in Real Time, [Paper], [Project]

• (arXiv 2022.10) RTFormer: Efficient Design for Real-Time Semantic Segmentation with Transformer, [Paper], [Code]

• (arXiv 2022.10) How to Train Vision Transformer on Small-scale Datasets?, [Paper], [Code]

• (arXiv 2022.10) Hate-CLIPper: Multimodal Hateful Meme Classification based on Cross-modal Interaction of CLIP Features, [Paper], [Code]

• (arXiv 2022.10) Large Models are Parsimonious Learners: Activation Sparsity in Trained Transformers, [Paper]

• (arXiv 2022.10) CURVED REPRESENTATION SPACE OF VISION TRANSFORMERS, [Paper]

• (arXiv 2022.10) Foundation Transformers, [Paper], [Code]

• (arXiv 2022.10) Underspecification in Scene Description-to-Depiction Tasks, [Paper]

• (arXiv 2022.10) Continuous conditional video synthesis by neural processes, [Paper], [Code]

• (arXiv 2022.10) SAIT: SPARSE VISION TRANSFORMERS THROUGH ADAPTIVE TOKEN PRUNING, [Paper]

• (arXiv 2022.10) ZITS++: Image Inpainting by Improving the Incremental Transformer on Structural Priors, [Paper]

• (arXiv 2022.10) SLOTFORMER: UNSUPERVISED VISUAL DYNAMICS SIMULATION WITH OBJECT-CENTRIC MODELS, [Paper], [Project]

• (arXiv 2022.10) Learning by Asking Questions for Knowledge-based Novel Object Recognition, [Paper]

• (arXiv 2022.10) Bridging the Gap Between Vision Transformers and Convolutional Neural Networks on Small Datasets, [Paper], [Code]

• (arXiv 2022.10) GGViT:Multistream Vision Transformer Network in Face2Face Facial Reenactment Detection, [Paper]

• (arXiv 2022.10) Distilling Knowledge from Language Models for Video-based Action Anticipation, [Paper]

• (arXiv 2022.10) Long-Form Video-Language Pre-Training with Multimodal Temporal Contrastive Learning, [Paper], [Code]

• (arXiv 2022.10) M3VIDEO: MASKED MOTION MODELING FOR SELFSUPERVISED VIDEO REPRESENTATION LEARNING, [Paper]

• (arXiv 2022.10) Uplift and Upsample: Efficient 3D Human Pose Estimation with Uplifting Transformers, [Paper], [Code]

• (arXiv 2022.10) FontTransformer: Few-shot High-resolution Chinese Glyph Image Synthesis via Stacked Transformers, [Paper]

• (arXiv 2022.10) AISFormer: Amodal Instance Segmentation with Transformer, [Paper], [Code]

• (arXiv 2022.10) ViewBirdiformer: Learning to recover ground-plane crowd trajectories and ego-motion from a single ego-centric view, [Paper]

• (arXiv 2022.10) One does not fit all! On the Complementarity of Vision Encoders for Vision and Language Tasks, [Paper]

• (arXiv 2022.10) PROMPT GENERATION NETWORKS FOR EFFICIENT ADAPTATION OF FROZEN VISION TRANSFORMERS, [Paper], [Code]

• (arXiv 2022.10) Generating Executable Action Plans with Environmentally-Aware Language Models, [Paper]

• (arXiv 2022.10) AVE-CLIP: AudioCLIP-based Multi-window Temporal Transformer for Audio Visual Event Localization, [Paper]

• (arXiv 2022.10) Improving Dense Contrastive Learning with Dense Negative Pairs, [Paper]

• (arXiv 2022.10) Fine-Grained Image Style Transfer with Visual Transformers, [Paper], [Code]

• (arXiv 2022.10) IT TAKES TWO: MASKED APPEARANCE-MOTION MODELING FOR SELF-SUPERVISED VIDEO TRANSFORMER PRE-TRAINING, [Paper]

• (arXiv 2022.10) Contrastive Video-Language Learning with Fine-grained Frame Sampling, [Paper]

• (arXiv 2022.10) Style-Guided Inference of Transformer for High-resolution Image Synthesis, [Paper]

• (arXiv 2022.10) MAP: Modality-Agnostic Uncertainty-Aware Vision-Language Pre-training Model, [Paper], [Code]

• (arXiv 2022.10) LEARNING TO LOCATE VISUAL ANSWER IN VIDEO CORPUS USING QUESTION, [Paper], [Code]

• (arXiv 2022.10) UNDERSTANDING EMBODIED REFERENCE WITH TOUCH-LINE TRANSFORMER, [Paper]

• (arXiv 2022.10) Point Transformer V2: Grouped Vector Attention and Partition-based Pooling, [Paper], [Code]

• (arXiv 2022.10) See, Plan, Predict: Language-guided Cognitive Planning with Video Prediction, [Paper]

• (arXiv 2022.10) USING BOTH DEMONSTRATIONS AND LANGUAGE INSTRUCTIONS TO EFFICIENTLY LEARN ROBOTIC TASKS, [Paper], [Project]

• (arXiv 2022.10) Generating image captions with external encyclopedic knowledge, [Paper]

• (arXiv 2022.10) LOCL: Learning Object-Attribute Composition using Localization, [Paper]

• (arXiv 2022.10) SVL-Adapter: Self-Supervised Adapter for Vision-Language Pretrained Models, [Paper], [Code]

• (arXiv 2022.10) ConTra: (Con)text (Tra)nsformer for Cross-Modal Video Retrieval, [Paper]

• (arXiv 2022.10) Learning Fine-Grained Visual Understanding for Video Question Answering via Decoupling Spatial-Temporal Modeling, [Paper], [Code]

• (arXiv 2022.10) (Fusionformer):Exploiting the Joint Motion Synergy with Fusion Network Based On Transformer for 3D Human Pose Estimation, [Paper]

• (arXiv 2022.10) Fast-ParC: Position Aware Global Kernel for ConvNets and ViTs, [Paper], [Code]

• (arXiv 2022.10) OGC: Unsupervised 3D Object Segmentation from Rigid Dynamics of Point Clouds, [Paper], [Code]

• (arXiv 2022.10) Multi-Modal Fusion Transformer for Visual Question Answering in Remote Sensing, [Paper], [Code]

• (arXiv 2022.10) Semantics-Consistent Cross-domain Summarization via Optimal Transport Alignment, [Paper]

• (arXiv 2022.10) VOLTA: VISION-LANGUAGE TRANSFORMER WITH WEAKLY-SUPERVISED LOCAL-FEATURE ALIGNMENT, [Paper]

• (arXiv 2022.10) OPEN-VOCABULARY SEMANTIC SEGMENTATION WITH MASK-ADAPTED CLIP, [Paper], [Project]

• (arXiv 2022.10) MAMO: Masked Multimodal Modeling for Fine-Grained Vision-Language Representation Learning, [Paper]

• (arXiv 2022.10) SELF-SUPERVISED VIDEO REPRESENTATION LEARNING WITH MOTION-AWARE MASKED AUTOENCODERS, [Paper], [Code]

• (arXiv 2022.10) LEARNING TO DECOMPOSE VISUAL FEATURES WITH LATENT TEXTUAL PROMPTS, [Paper]

• (arXiv 2022.10) DCVQE: A Hierarchical Transformer for Video Quality Assessment, [Paper]

• (arXiv 2022.10) Fine-grained Object Categorization for Service Robots, [Paper]

• (arXiv 2022.10) CLIP-DIFFUSION-LM: APPLY DIFFUSION MODEL ON IMAGE CAPTIONING, [Paper], [Code]

• (arXiv 2022.10) A Memory Transformer Network for Incremental Learning, [Paper]

• (arXiv 2022.10) Bridging CLIP and StyleGAN through Latent Alignment for Image Editing, [Paper]

• (arXiv 2022.10) LMQFormer: A Laplace-Prior-Guided Mask Query Transformer for Lightweight Snow Removal, [Paper]

• (arXiv 2022.10) FS-DETR: FEW-SHOT DETECTION TRANSFORMER WITH PROMPTING AND WITHOUT RE-TRAINING, [Paper]

• (arXiv 2022.10) Transformer-based Localization from Embodied Dialog with Large-scale Pre-training, [Paper]

• (arXiv 2022.10) Turbo Training with Token Dropout, [Paper]

• (arXiv 2022.10) Polyhistor: Parameter-Efficient Multi-Task Adaptation for Dense Vision Tasks, [Paper]

• (arXiv 2022.10) C2KD: Cross-Lingual Cross-Modal Knowledge Distillation for Multilingual Text-Video Retrieval, [Paper]

• (arXiv 2022.10) Pose Guided Human Image Synthesis with Partially Decoupled GAN, [Paper]

• (arXiv 2022.10) A Simple Plugin for Transforming Images to Arbitrary Scales, [Paper], [Project]

• (arXiv 2022.10) Time-Space Transformers for Video Panoptic Segmentation, [Paper]

• (arXiv 2022.10) MOAT: ALTERNATING MOBILE CONVOLUTION AND ATTENTION BRINGS STRONG VISION MODELS, [Paper], [Code]

• (arXiv 2022.10) IMAGEN VIDEO: HIGH DEFINITION VIDEO GENERATION WITH DIFFUSION MODELS, [Paper], [Project]

• (arXiv 2022.10) clip2latent: Text driven sampling of a pre-trained StyleGAN using denoising diffusion and CLIP, [Paper]

• (arXiv 2022.10) FQDet: Fast-converging Query-based Detector, [Paper], [Code]

• (arXiv 2022.10) VARIATIONAL PROMPT TUNING IMPROVES GENERALIZATION OF VISION-LANGUAGE MODELS, [Paper]

• (arXiv 2022.10) Grounding Language with Visual Affordances over Unstructured Data, [Paper], [Project]

• (arXiv 2022.10) Granularity-aware Adaptation for Image Retrieval over Multiple Tasks, [Paper]

• (arXiv 2022.10) WHEN AND WHY VISION-LANGUAGE MODELS BEHAVE LIKE BAGS-OF-WORDS, AND WHAT TO DO ABOUT IT? [Paper]

• (arXiv 2022.10) Multi-view Human Body Mesh Translator, [Paper]

• (arXiv 2022.10) EXPLORING THE ROLE OF MEAN TEACHERS IN SELFSUPERVISED MASKED AUTO-ENCODERS, [Paper]

• (arXiv 2022.10) Point Cloud Recognition with Position-to-Structure Attention Transformers, [Paper]

• (arXiv 2022.10) TEMPORALLY CONSISTENT VIDEO TRANSFORMER FOR LONG-TERM VIDEO PREDICTION, [Paper], [Code]

• (arXiv 2022.10) PHENAKI: VARIABLE LENGTH VIDEO GENERATION FROM OPEN DOMAIN TEXTUAL DESCRIPTIONS, [Paper]

• (arXiv 2022.10) MuRAG: Multimodal Retrieval-Augmented Generator for Open Question Answering over Images and Text, [Paper]

• (arXiv 2022.10) Real-World Robot Learning with Masked Visual Pre-training, [Paper], [Project]

• (arXiv 2022.10) BaseTransformers: Attention over base data-points for One Shot Learning, [Paper], [Code]

• (arXiv 2022.10) Focal and Global Spatial-Temporal Transformer for Skeleton-based Action Recognition, [Paper]

• (arXiv 2022.10) Vision Transformer Based Model for Describing a Set of Images as a Story, [Paper]

• (arXiv 2022.10) Video Referring Expression Comprehension via Transformer with Content-aware Query, [Paper], [Code]

• (arXiv 2022.10) EFFECTIVE SELF-SUPERVISED PRE-TRAINING ON LOW-COMPUTE NETWORKS WITHOUT DISTILLATION, [Paper]

• (arXiv 2022.10) CLIP MODEL IS AN EFFICIENT CONTINUAL LEARNER, [Paper]

• (arXiv 2022.10) Content-Based Search for Deep Generative Models, [Paper]

• (arXiv 2022.10) MAPLE: MULTI-MODAL PROMPT LEARNING, [Paper], [Code]

• (arXiv 2022.10) SYSTEMATIC GENERALIZATION AND EMERGENT STRUCTURES IN TRANSFORMERS TRAINED ON STRUCTURED TASKS, [Paper]

• (arXiv 2022.10) WIDE ATTENTION IS THE WAY FORWARD FOR TRANSFORMERS? [Paper]

• (arXiv 2022.10) DARTFORMER: FINDING THE BEST TYPE OF ATTENTION, [Paper]

• (arXiv 2022.10) MOBILEVITV3: MOBILE-FRIENDLY VISION TRANSFORMER WITH SIMPLE AND EFFECTIVE FUSION OF LOCAL, GLOBAL AND INPUT FEATURES, [Paper], [Code]

• (arXiv 2022.10) Differentiable Parsing and Visual Grounding of Verbal Instructions for Object Placement, [Paper], [Project]

• (arXiv 2022.10) EAPruning: Evolutionary Pruning for Vision Transformers and CNNs, [Paper]

• (arXiv 2022.10) Motion-inductive Self-supervised Object Discovery in Videos, [Paper]

• (arXiv 2022.10) Fully Transformer Network for Change Detection of Remote Sensing Images, [Paper], [Code]

• (arXiv 2022.10) TOWARDS A UNIFIED VIEW ON VISUAL PARAMETER-EFFICIENT TRANSFER LEARNING, [Paper]

• (arXiv 2022.10) Visual Prompt Tuning for Generative Transfer Learning, [Paper]

• (arXiv 2022.10) A Strong Transfer Baseline for RGB-D Fusion in Vision Transformers, [Paper]

• (arXiv 2022.10) LPT: LONG-TAILED PROMPT TUNING FOR IMAGE CLASSIFICATION, [Paper]

• (arXiv 2022.10) Expediting Large-Scale Vision Transformer for Dense Prediction without Fine-tuning, [Paper]

• (arXiv 2022.10) CLIP2POINT: TRANSFER CLIP TO POINT CLOUD CLASSIFICATION WITH IMAGE-DEPTH PRE-TRAINING, [Paper]

• (arXiv 2022.10) Dual-former: Hybrid Self-attention Transformer for Efficient Image Restoration, [Paper]

• (arXiv 2022.10) LANGUAGE-AWARE SOFT PROMPTING FOR VISION & LANGUAGE FOUNDATION MODELS, [Paper]

• (arXiv 2022.10) ASIF: COUPLED DATA TURNS UNIMODAL MODELS TO MULTIMODAL WITHOUT TRAINING, [Paper]

• (arXiv 2022.10) ImmFusion: Robust mmWave-RGB Fusion for 3D Human Body Reconstruction in All Weather Conditions, [Paper]

• (arXiv 2022.10) PROMPT LEARNING WITH OPTIMAL TRANSPORT FOR VISION-LANGUAGE MODELS, [Paper]

• (arXiv 2022.10) Bridged Transformer for Vision and Point Cloud 3D Object Detection, [Paper]

• (arXiv 2022.10) Dense Prediction Transformer for Scale Estimation in Monocular Visual Odometry, [Paper]

• (arXiv 2022.10) HUMAN MOTION DIFFUSION MODEL, [Paper], [Project]

• (arXiv 2022.10) TokenFlow: Rethinking Fine-grained Cross-modal Alignment in Vision-Language Retrieval, [Paper]

• (arXiv 2022.10) UniCLIP: Unified Framework for Contrastive Language–Image Pre-training, [Paper]

• (arXiv 2022.10) CrossDTR: Cross-view and Depth-guided Transformers for 3D Object Detection, [Paper], [Code]

• (arXiv 2022.10) Multi-dataset Training of Transformers for Robust Action Recognition, [Paper], [Code]

• (arXiv 2022.10) Multi-Scale Human-Object Interaction Detector, [Paper]

• (arXiv 2022.10) LGDN: Language-Guided Denoising Network for Video-Language Modeling, [Paper]

• (arXiv 2022.10) RaP: Redundancy-aware Video-language Pre-training for Text-Video Retrieval, [Paper], [Code]

• (arXiv 2022.10) Intermediate Prototype Mining Transformer for Few-Shot Semantic Segmentation, [Paper], [Code]

• (arXiv 2022.10) Decoding Visual Neural Representations by Multimodal Learning of Brain-Visual-Linguistic Features, [Paper], [Code]

• (arXiv 2022.10) Q-ViT: Accurate and Fully Quantized Low-bit Vision Transformer, [Paper], [Code]

• (arXiv 2022.10) Prepended Domain Transformer: Heterogeneous Face Recognition without Bells and Whistles, [Paper]

• (arXiv 2022.10) Visual Knowledge Graph for Human Action Reasoning in Videos, [Paper]

• (arXiv 2022.10) Human Joint Kinematics Diffusion-Refinement for Stochastic Motion Prediction, [Paper]

• (arXiv 2022.10) VIMA: GENERAL ROBOT MANIPULATION WITH MULTIMODAL PROMPTS, [Paper], [Project]

• (arXiv 2022.10) What Should the System Do Next?: Operative Action Captioning for Estimating System Actions, [Paper]

• (arXiv 2022.10) DMMGAN: Diverse Multi Motion Prediction of 3D Human Joints using Attention-Based Generative Adversarial Network, [Paper]

• (arXiv 2022.10) PIZZA: A Powerful Image-only Zero-Shot Zero-CAD Approach to 6 DoF Tracking, [Paper], [Code]

2022.09

• (arXiv 2022.09) SELF-DISTILLATION FOR FURTHER PRE-TRAINING OF TRANSFORMERS, [Paper]

• (arXiv 2022.09) Visuo-Tactile Transformers for Manipulation, [Paper], [Project]

• (arXiv 2022.09) UNDERSTANDING PURE CLIP GUIDANCE FOR VOXEL GRID NERF MODELS, [Paper], [Project]

• (arXiv 2022.09) Dual Progressive Transformations for Weakly Supervised Semantic Segmentation, [Paper], [Code]

• (arXiv 2022.09) Transformers for Object Detection in Large Point Clouds, [Paper]

• (arXiv 2022.09) DIFFUSION-BASED IMAGE TRANSLATION USING DISENTANGLED STYLE AND CONTENT REPRESENTATION, [Paper]

• (arXiv 2022.09) ERNIE-VIL 2.0: MULTI-VIEW CONTRASTIVE LEARNING FOR IMAGE-TEXT PRE-TRAINING, [Paper], [Code]

• (arXiv 2022.09) LEARNING TRANSFERABLE SPATIOTEMPORAL REPRESENTATIONS FROM NATURAL SCRIPT KNOWLEDGE, [Paper]

• (arXiv 2022.09) SMALLCAP: Lightweight Image Captioning Prompted with Retrieval Augmentation, [Paper], [Code]

• (arXiv 2022.09) SPIKFORMER: WHEN SPIKING NEURAL NETWORK MEETS TRANSFORMER, [Paper]

• (arXiv 2022.09) F-VLM: OPEN-VOCABULARY OBJECT DETECTION UPON FROZEN VISION AND LANGUAGE MODELS, [Paper]

• (arXiv 2022.09) CONTRASTIVE CORPUS ATTRIBUTION FOR EXPLAINING REPRESENTATIONS, [Paper]

• (arXiv 2022.09) Alignment-guided Temporal Attention for Video Action Recognition, [Paper]

• (arXiv 2022.09) EDA: Explicit Text-Decoupling and Dense Alignment for 3D Visual and Language Learning, [Paper], [Code]

• (arXiv 2022.09) SPOTLIGHT: MOBILE UI UNDERSTANDING USING VISION-LANGUAGE MODELS WITH A FOCUS, [Paper]

• (arXiv 2022.09) DREAMFUSION: TEXT-TO-3D USING 2D DIFFUSION, [Paper], [Project]

• (arXiv 2022.09) REST: RETRIEVE & SELF-TRAIN FOR GENERATIVE ACTION RECOGNITION, [Paper]

• (arXiv 2022.09) Effective Vision Transformer Training: A Data-Centric Perspective, [Paper]

• (arXiv 2022.09) Human-in-the-loop Robotic Grasping using BERT Scene Representation, [Paper], [Project]

• (arXiv 2022.09) Revisiting Few-Shot Learning from a Causal Perspective, [Paper]

• (arXiv 2022.09) Attacking Compressed Vision Transformers, [Paper]

• (arXiv 2022.09) Adaptive Sparse ViT: Towards Learnable Adaptive Token Pruning by Fully Exploiting Self-Attention, [Paper]

• (arXiv 2022.09) DeViT: Deformed Vision Transformers in Video Inpainting, [Paper]

• (arXiv 2022.09) Obj2Seq: Formatting Objects as Sequences with Class Prompt for Visual Tasks, [Paper], [Code]

• (arXiv 2022.09) Dynamic MDETR: A Dynamic Multimodal Transformer Decoder for Visual Grounding, [Paper]

• (arXiv 2022.09) Motion Transformer for Unsupervised Image Animation, [Paper]

• (arXiv 2022.09) Weighted Contrastive Hashing, [Paper], [Code]

• (arXiv 2022.09) CALIP: Zero-Shot Enhancement of CLIP with Parameter-free Attention, [Paper]

• (arXiv 2022.09) Dialog Acts for Task-Driven Embodied Agents, [Paper]

• (arXiv 2022.09) NEURAL MARIONETTE: A Transformer-based Multi-action Human Motion Synthesis System, [Paper], [Code]

• (arXiv 2022.09) Embracing Consistency: A One-Stage Approach for Spatio-Temporal Video Grounding, [Paper], [Code]

• (arXiv 2022.09) Text-Adaptive Multiple Visual Prototype Matching for Video-Text Retrieval, [Paper]

• (arXiv 2022.09) Towards Parameter-Efficient Integration of Pre-Trained Language Models In Temporal Video Grounding, [Paper]

• (arXiv 2022.09) Anomaly Detection in Aerial Videos with Transformers, [Paper], [Code]

• (arXiv 2022.09) AdaFocusV3: On Unified Spatial-temporal Dynamic Video Recognition, [Paper]

• (arXiv 2022.09) Motion Transformer with Global Intention Localization and Local Movement Refinement, [Paper], [Code]

• (arXiv 2022.09) FREESEG: FREE MASK FROM INTERPRETABLE CONTRASTIVE LANGUAGE-IMAGE PRETRAINING FOR SEMANTIC SEGMENTATION, [Paper]

• (arXiv 2022.09) Learning State-Aware Visual Representations from Audible Interactions, [Paper], [Code]

• (arXiv 2022.09) Towards Explainable 3D Grounded Visual Question Answering: A New Benchmark and Strong Baseline, [Paper]

• (arXiv 2022.09) Leveraging Self-Supervised Training for Unintentional Action Recognition, [Paper]

• (arXiv 2022.09) NeRF-Loc: Transformer-Based Object Localization Within Neural Radiance Fields, [Paper]

• (arXiv 2022.09) All are Worth Words: a ViT Backbone for Score-based Diffusion Models, [Paper]

• (arXiv 2022.09) Paraphrasing Is All You Need for Novel Object Captioning, [Paper]

• (arXiv 2022.09) Collaboration of Pre-trained Models Makes Better Few-shot Learner, [Paper]

• (arXiv 2022.09) Multi-modal Video Chapter Generation, [Paper], [Code]

• (arXiv 2022.09) Best Prompts for Text-to-Image Models and How to Find Them, [Paper]

• (arXiv 2022.09) Swin2SR: SwinV2 Transformer for Compressed Image Super-Resolution and Restoration, [Paper], [Code]

• (arXiv 2022.09) 3DPCT: 3D Point Cloud Transformer with Dual Self-attention, [Paper]

• (arXiv 2022.09) LIGHTWEIGHT TRANSFORMERS FOR HUMAN ACTIVITY RECOGNITION ON MOBILE DEVICES, [Paper]

• (arXiv 2022.09) PACT: Perception-Action Causal Transformer for Autoregressive Robotics Pre-Training, [Paper]

• (arXiv 2022.09) UniColor: A Unified Framework for Multi-Modal Colorization with Transformer, [Paper], [Code]

• (arXiv 2022.09) Traffic Accident Risk Forecasting using Contextual Vision Transformers, [Paper]

• (arXiv 2022.09) CONE: An Efficient COarse-to-fiNE Alignment Framework for Long Video Temporal Grounding, [Paper]

• (arXiv 2022.09) Recipe Generation from Unsegmented Cooking Videos, [Paper]

• (arXiv 2022.09) PicT: A Slim Weakly Supervised Vision Transformer for Pavement Distress Classification, [Paper], [Code]

• (arXiv 2022.09) Show, Interpret and Tell: Entity-aware Contextualised Image Captioning in Wikipedia, [Paper]

• (arXiv 2022.09) RNGDet++: Road Network Graph Detection by Transformer with Instance Segmentation and Multi-scale Features Enhancement, [Paper], [Code]

• (arXiv 2022.09) Toward 3D Spatial Reasoning for Human-like Text-based Visual Question Answering, [Paper]

• (arXiv 2022.09) I2DFormer: Learning Image to Document Attention for Zero-Shot Image Classification, [Paper]

• (arXiv 2022.09) Integer Fine-tuning of Transformer-based Models, [Paper]

• (arXiv 2022.09) Open-vocabulary Queryable Scene Representations for Real World Planning, [Paper], [Code]

• (arXiv 2022.09) DetCLIP: Dictionary-Enriched Visual-Concept Paralleled Pre-training for Open-world Detection, [Paper]

• (arXiv 2022.09) Hierarchical Temporal Transformer for 3D Hand Pose Estimation and Action Recognition from Egocentric RGB Videos, [Paper]

• (arXiv 2022.09) Graph Reasoning Transformer for Image Parsing, [Paper]

• (arXiv 2022.09) Quantum Vision Transformers, [Paper]

• (arXiv 2022.09) Active Visual Search in the Wild, [Paper]

• (arXiv 2022.09) PPT: token-Pruned Pose Transformer for monocular and multi-view human pose estimation, [Paper], [Code]

• (arXiv 2022.09) Learning Distinct and Representative Modes for Image Captioning, [Paper], [Code]

• (arXiv 2022.09) TODE-Trans: Transparent Object Depth Estimation with Transformer, [Paper], [Code]

• (arXiv 2022.09) Tree-based Text-Vision BERT for Video Search in Baidu Video Advertising, [Paper]

• (arXiv 2022.09) Integrative Feature and Cost Aggregation with Transformers for Dense Correspondence, [Paper]

• (arXiv 2022.09) Axially Expanded Windows for Local-Global Interaction in Vision Transformers, [Paper]

• (arXiv 2022.09) UNCERTAINTY AWARE MULTITASK PYRAMID VISION TRANSFORMER FOR UAV-BASED OBJECT RE-IDENTIFICATION, [Paper]

• (arXiv 2022.09) TASKED: Transformer-based Adversarial learning for human activity recognition using wearable sensors via Self-KnowledgE Distillation, [Paper]

• (arXiv 2022.09) EcoFormer: Energy-Saving Attention with Linear Complexity, [Paper], [[Code]]](https://github.com/ziplab/EcoFormer)

• (arXiv 2022.09) Panoramic Vision Transformer for Saliency Detection in 360◦ Videos, [Paper]

• (arXiv 2022.09) THE BIASED ARTIST: EXPLOITING CULTURAL BIASES VIA HOMOGLYPHS IN TEXT-GUIDED IMAGE GENERATION MODELS, [Paper]

• (arXiv 2022.09) Scene Graph Modification as Incremental Structure Expanding, [Paper], [Code]

• (arXiv 2022.09) Discriminative Sampling of Proposals in Self-Supervised Transformers for Weakly Supervised Object Localization, [Paper], [Code]

• (arXiv 2022.09) Real-time Online Video Detection with Temporal Smoothing Transformers, [Paper]

• (arXiv 2022.09) ViT-DD: Multi-Task Vision Transformer for Semi-Supervised Driver Distraction Detection, [Paper], [Code]

• (arXiv 2022.09) Code as Policies: Language Model Programs for Embodied Control, [Paper], [Project]

• (arXiv 2022.09) SQ-Swin: a Pretrained Siamese Quadratic Swin Transformer for Lettuce Browning Prediction, [Paper]

• (arXiv 2022.09) Self-Attentive Pooling for Efficient Deep Learning, [Paper]

• (arXiv 2022.09) Domain-Unified Prompt Representations for Source-Free Domain Generalization, [Paper], [Code]

• (arXiv 2022.09) BRIDGING THE GAP TO REAL-WORLD OBJECTCENTRIC LEARNING, [Paper]

• (arXiv 2022.09) Prompt-guided Scene Generation for 3D Zero-Shot Learning, [Paper]

• (arXiv 2022.09) RE-IMAGEN: RETRIEVAL-AUGMENTED TEXT-TO-IMAGE GENERATOR, [Paper]

• (arXiv 2022.09) Distribution Aware Metrics for Conditional Natural Language Generation, [Paper]

• (arXiv 2022.09) CLIPping Privacy: Identity Inference Attacks on Multi-Modal Machine Learning Models, [Paper]

• (arXiv 2022.09) Finetuning Pretrained Vision-Language Models with Correlation Information Bottleneck for Robust Visual Question Answering, [Paper]

• (arXiv 2022.09) PriorLane: A Prior Knowledge Enhanced Lane Detection Approach Based on Transformer, [Paper], [Code]

• (arXiv 2022.09) Can We Solve 3D Vision Tasks Starting from A 2D Vision Transformer? [Paper], [Code]

• (arXiv 2022.09) EXPLORING VISUAL INTERPRETABILITY FOR CONTRASTIVE LANGUAGE-IMAGE PRE-TRAINING, [Paper]

• (arXiv 2022.09) OmniVL: One Foundation Model for Image-Language and Video-Language Tasks, [Paper]

• (arXiv 2022.09) Test-Time Training with Masked Autoencoders, [Paper], [Code]

• (arXiv 2022.09) VISUAL RECOGNITION WITH DEEP NEAREST CENTROIDS, [Paper], [Code]

• (arXiv 2022.09) One-Shot Transfer of Affordance Regions? AffCorrs! [Paper], [Code]

• (arXiv 2022.09) Test-Time Prompt Tuning for Zero-Shot Generalization in Vision-Language Models, [Paper], [Code]

• (arXiv 2022.09) A Light Recipe to Train Robust Vision Transformers, [Paper], [Code]

• (arXiv 2022.09) On the Surprising Effectiveness of Transformers in Low-Labeled Video Recognition, [Paper]

• (arXiv 2022.09) Number of Attention Heads vs. Number of Transformer-Encoders in Computer Vision, [Paper]

• (arXiv 2022.09) Global Semantic Descriptors for Zero-Shot Action Recognition, [Paper], [Code]

• (arXiv 2022.09) Revisiting Neural Scaling Laws in Language and Vision, [Paper]

• (arXiv 2022.09) Small Transformers Compute Universal Metric Embeddings, [Paper]

• (arXiv 2022.09) CLIP-ViP: Adapting Pre-trained Image-Text Model to Video-Language Representation Alignment, [Paper], [Code]

• (arXiv 2022.09) CRAFT: Camera-Radar 3D Object Detection with Spatio-Contextual Fusion Transformer, [Paper]

• (arXiv 2022.09) Transformers and CNNs both Beat Humans on SBIR, [Paper]

• (arXiv 2022.09) PaLI: A Jointly-Scaled Multilingual Language-Image Model, [Paper]

• (arXiv 2022.09) MUST-VQA: MUltilingual Scene-text VQA, [Paper], [Code]

• (arXiv 2022.09) Leveraging Large Language Models for Robot 3D Scene Understanding, [Paper], [Code]

• (arXiv 2022.09) A lightweight Transformer-based model for fish landmark detection, [Paper]

• (arXiv 2022.09) PSAQ-ViT V2: Towards Accurate and General Data-Free Quantization for Vision Transformers, [Paper], [Code]

• (arXiv 2022.09) ComplETR: Reducing the cost of annotations for object detection in dense scenes with vision transformers, [Paper]

• (arXiv 2022.09) Semantic2Graph: Graph-based Multi-modal Feature for Action Segmentation in Videos, [Paper]

• (arXiv 2022.09) CenterFormer: Center-based Transformer for 3D Object Detection, [Paper], [Code]

• (arXiv 2022.09) PreSTU: Pre-Training for Scene-Text Understanding, [Paper]

• (arXiv 2022.09) OmDet: Language-Aware Object Detection with Large-scale Vision-Language Multi-dataset Pre-training, [Paper]

• (arXiv 2022.09) DMTNet: Dynamic Multi-scale Network for Dual-pixel Images Defocus Deblurring with Transformer, [Paper]

• (arXiv 2022.09) SeRP: Self-Supervised Representation Learning Using Perturbed Point Clouds, [Paper]

• (arXiv 2022.09) VL-Taboo: An Analysis of Attribute-based Zero-shot Capabilities of Vision-Language Models, [Paper]

• (arXiv 2022.09) StoryDALL-E: Adapting Pretrained Text-to-Image Transformers for Story Continuation, [Paper], [Code]

• (arXiv 2022.09) ON THE COMPUTATIONAL COMPLEXITY OF SELF-ATTENTION, [Paper]

• (arXiv 2022.09) Instruction-driven history-aware policies for robotic manipulations, [Paper], [Code]

• (arXiv 2022.09) Towards Multi-Lingual Visual Question Answering, [Paper]

• (arXiv 2022.09) PERCEIVER-ACTOR: A Multi-Task Transformer for Robotic Manipulation, [Paper], [Project]

• (arXiv 2022.09) GLOBAL PROTOTYPE ENCODING FOR INCREMENTAL VIDEO HIGHLIGHTS DETECTION, [Paper], [Code]

• (arXiv 2022.09) Self-Supervised Multimodal Fusion Transformer for Passive Activity Recognition, [Paper]

• (arXiv 2022.09) FETA: Towards Specializing Foundation Models for Expert Task Applications, [Paper]

• (arXiv 2022.09) Prior Knowledge-Guided Attention in Self-Supervised Vision Transformers, [Paper]

• (arXiv 2022.09) Exploring Target Representations for Masked Autoencoders, [Paper]

• (arXiv 2022.09) ISS: IMAGE AS STEPPING STONE FOR TEXT-GUIDED 3D SHAPE GENERATION, [Paper]

• (arXiv 2022.09) Towards Confidence-guided Shape Completion for Robotic Applications, [Paper], [Code]

• (arXiv 2022.09) Pre-training image-language transformers for open-vocabulary tasks, [Paper]

• (arXiv 2022.09) Improved Masked Image Generation with Token-Critic, [Paper]

• (arXiv 2022.09) Do As I Can, Not As I Say: Grounding Language in Robotic Affordances, [Paper], [Code]

• (arXiv 2022.09) Uformer-ICS: A Specialized U-Shaped Transformer for Image Compressive Sensing, [Paper]

• (arXiv 2022.09) An Empirical Study of End-to-End Video-Language Transformers with Masked Visual Modeling, [Paper]

• (arXiv 2022.09) Spatial-Temporal Transformer for Video Snapshot Compressive Imaging, [Paper], [Code]

• (arXiv 2022.09) MAFormer: A Transformer Network with Multi-scale Attention Fusion for Visual Recognition, [Paper]

• (arXiv 2022.09) SEFormer: Structure Embedding Transformer for 3D Object Detection, [Paper]

• (arXiv 2022.09) ADTR: Anomaly Detection Transformer with Feature Reconstruction, [Paper]

• (arXiv 2022.09) Learning Canonical Embeddings for Unsupervised Shape Correspondence with Locally Linear Transformations, [Paper]

• (arXiv 2022.09) Transformer-CNN Cohort: Semi-supervised Semantic Segmentation by the Best of Both Students, [Paper]

• (arXiv 2022.09) PTSEFormer: Progressive Temporal-Spatial Enhanced TransFormer Towards Video Object Detection, [Paper], [Code]

• (arXiv 2022.09) VITKD: PRACTICAL GUIDELINES FOR VIT FEATURE KNOWLEDGE DISTILLATION, [Paper], [Code]

• (arXiv 2022.09) DPIT: Dual-Pipeline Integrated Transformer for Human Pose Estimation, [Paper]

• (arXiv 2022.09) SkeletonMAE: Spatial-Temporal Masked Autoencoders for Self-supervised Skeleton Action Recognition, [Paper]

• (arXiv 2022.09) What does a platypus look like? Generating customized prompts for zero-shot image classification, [Paper], [Code]

• (arXiv 2022.09) AI Illustrator: Translating Raw Descriptions into Images by Prompt-based Cross-Modal Generation, [Paper], [Code]

• (arXiv 2022.09) MimCo: Masked Image Modeling Pre-training with Contrastive Teacher, [Paper]

• (arXiv 2022.09) Multi-modal Contrastive Representation Learning for Entity Alignment, [Paper]

• (arXiv 2022.09) Zero-Shot Multi-Modal Artist-Controlled Retrieval and Exploration of 3D Object Sets, [Paper]

• (arXiv 2022.09) Geometry Aligned Variational Transformer for Image-conditioned Layout Generation, [Paper]

• (arXiv 2022.09) Real-time 3D Single Object Tracking with Transformer, [Paper], [Code]

• (arXiv 2022.09) Video-Guided Curriculum Learning for Spoken Video Grounding, [Paper], [Code]

• (arXiv 2022.09) FLAME: Free-form Language-based Motion Synthesis & Editing, [Paper]

• (arXiv 2022.09) TOKENCUT: SEGMENTING OBJECTS IN IMAGES AND VIDEOS WITH SELF-SUPERVISED TRANSFORMER AND NORMALIZED CUT, [Paper], [Code]

• (arXiv 2022.09) Unified Fully and Timestamp Supervised Temporal Action Segmentation via Sequence to Sequence Translation, [Paper]

• (arXiv 2022.09) MAPLE: Masked Pseudo-Labeling autoEncoder for Semi-supervised Point Cloud Action Recognition, [Paper], [Project]

• (arXiv 2022.09) Visual Prompting via Image Inpainting, [Paper], [Project]

• (arXiv 2022.09) RLIP: Relational Language-Image Pre-training for Human-Object Interaction Detection, [Paper], [Code]

2022.08

• (arXiv 2022.08) On Grounded Planning for Embodied Tasks with Language Models, [Paper], [Project]

• (arXiv 2022.08) Group Activity Recognition in Basketball Tracking Data - Neural Embeddings in Team Sports (NETS), [Paper]

• (arXiv 2022.08) SWIN-TRANSFORMER-YOLOV5 FOR REAL-TIME WINE GRAPE BUNCH DETECTION, [Paper]

• (arXiv 2022.08) SIM-Trans: Structure Information Modeling Transformer for Fine-grained Visual Categorization, [Paper], [Code]

• (arXiv 2022.08) INJECTING IMAGE DETAILS INTO CLIP’S FEATURE SPACE, [Paper]

• (arXiv 2022.08) Hierarchical Local-Global Transformer for Temporal Sentence Grounding, [Paper]

• (arXiv 2022.08) EViT: Privacy-Preserving Image Retrieval via Encrypted Vision Transformer in Cloud Computing, [Paper]

• (arXiv 2022.08) TRUST: An Accurate and End-to-End Table structure Recognizer Using Splitting-based Transformers, [Paper]

• (arXiv 2022.08) ELMformer: Efficient Raw Image Restoration with a Locally Multiplicative Transformer, [Paper], [Code]

• (arXiv 2022.08) SoMoFormer: Multi-Person Pose Forecasting with Transformers, [Paper]

• (arXiv 2022.08) A Circular Window-based Cascade Transformer for Online Action Detection, [Paper]

• (arXiv 2022.08) ASpanFormer: Detector-Free Image Matching with Adaptive Span Transformer, [Paper]

• (arXiv 2022.08) Robust Sound-Guided Image Manipulation, [Paper]

• (arXiv 2022.08) TrojViT: Trojan Insertion in Vision Transformers, [Paper]

• (arXiv 2022.08) User-Controllable Latent Transformer for StyleGAN Image Layout Editing, [Paper]

• (arXiv 2022.08) Few-Shot Learning Meets Transformer: Unified Query-Support Transformers for Few-Shot Classification, [Paper]

• (arXiv 2022.08) JARVIS: A Neuro-Symbolic Commonsense Reasoning Framework for Conversational Embodied Agents, [Paper]

• (arXiv 2022.08) TFusion: Transformer based N-to-One Multimodal Fusion Block, [Paper]

• (arXiv 2022.08) VMFormer: End-to-End Video Matting with Transformer, [Paper], [Code]

• (arXiv 2022.08) LOGICRANK: Logic Induced Reranking for Generative Text-to-Image Systems, [Paper]

• (arXiv 2022.08) CLUSTR: EXPLORING EFFICIENT SELF-ATTENTION VIA CLUSTERING FOR VISION TRANSFORMERS, [Paper]

• (arXiv 2022.08) Federated Zero-Shot Learning with Mid-Level Semantic Knowledge Transfer, [Paper]

• (arXiv 2022.08) Prompt Tuning with Soft Context Sharing for Vision-Language Models, [Paper]

• (arXiv 2022.08) Efficient Vision-Language Pretraining with Visual Concepts and Hierarchical Alignment, [Paper], [Code]

• (arXiv 2022.08) CounTR: Transformer-based Generalised Visual Counting, [Paper], [Code]

• (arXiv 2022.08) Open-Set Semi-Supervised Object Detection, [Paper]

• (arXiv 2022.08) gSwin: Gated MLP Vision Model with Hierarchical Structure of Shifted Window, [Paper]

• (arXiv 2022.08) Adaptive Perception Transformer for Temporal Action Localization, [Paper], [Code]

• (arXiv 2022.08) Symbolic Replay: Scene Graph as Prompt for Continual Learning on VQA Task, [Paper], [Code]

• (arXiv 2022.08) Masked Autoencoders Enable Efficient Knowledge Distillers, [Paper], [Code]

• (arXiv 2022.08) LaTeRF: Label and Text Driven Object Radiance Fields, [Paper]

• (arXiv 2022.08) Video Mobile-Former: Video Recognition with Efficient Global Spatial-temporal Modeling, [Paper]

• (arXiv 2022.08) Pix4Point: Image Pretrained Transformers for 3D Point Cloud Understanding, [Paper], [Code]

• (arXiv 2022.08) MaskCLIP: Masked Self-Distillation Advances Contrastive Language-Image Pretraining, [Paper]

• (arXiv 2022.08) Visual Subtitle Feature Enhanced Video Outline Generation, [Paper], [Code]

• (arXiv 2022.08) CATS: COMPLEMENTARY CNN AND TRANSFORMER ENCODERS FOR SEGMENTATION, [Paper]

• (arXiv 2022.08) Modeling Paragraph-Level Vision-Language Semantic Alignment for Multi-Modal Summarization, [Paper]

• (arXiv 2022.08) FashionVQA: A Domain-Specific Visual Question Answering System, [Paper]

• (arXiv 2022.08) K-ORDER GRAPH-ORIENTED TRANSFORMER WITH GRAATTENTION FOR 3D POSE AND SHAPE ESTIMATION, [Paper]

• (arXiv 2022.08) Towards Efficient Use of Multi-Scale Features in Transformer-Based Object Detectors, [Paper], [Code]

• (arXiv 2022.08) Improving video retrieval using multilingual knowledge transfer, [Paper]

• (arXiv 2022.08) EFFICIENT SPARSELY ACTIVATED TRANSFORMERS, [Paper]

• (arXiv 2022.08) M2HF: MULTI-LEVEL MULTI-MODAL HYBRID FUSION FOR TEXT-VIDEO RETRIEVAL, [Paper]

• (arXiv 2022.08) Accelerating Vision Transformer Training via a Patch Sampling Schedule, [Paper], [Project]

• (arXiv 2022.08) A Dual Modality Approach For (Zero-Shot) Multi-Label Classification, [Paper]

• (arXiv 2022.08) Offline Handwritten Mathematical Recognition using Adversarial Learning and Transformers, [Paper]

• (arXiv 2022.08) Semantic-enhanced Image Clustering, [Paper]

• (arXiv 2022.08) DPTNet: A Dual-Path Transformer Architecture for Scene Text Detection, [Paper]

• (arXiv 2022.08) ProtoPFormer: Concentrating on Prototypical Parts in Vision Transformers for Interpretable Image Recognition, [Paper], [Code]

• (arXiv 2022.08) Image as a Foreign Language: BEIT Pretraining for All Vision and Vision-Language Tasks, [Paper], [Project]

• (arXiv 2022.08) PoseBERT: A Generic Transformer Module for Temporal 3D Human Modeling, [Paper], [Code]

• (arXiv 2022.08) EFFICIENT ATTENTION-FREE VIDEO SHIFT TRANSFORMERS, [Paper]

• (arXiv 2022.08) Flat Multi-modal Interaction Transformer for Named Entity Recognition, [Paper]

• (arXiv 2022.08) Dance Style Transfer with Cross-modal Transformer, [Paper]

• (arXiv 2022.08) Improved Image Classification with Token Fusion , [Paper]

• (arXiv 2022.08) VAuLT: Augmenting the Vision-and-Language Transformer with the Propagation of Deep Language Representations, [Paper], [Code]

• (arXiv 2022.08) TEXT TO IMAGE GENERATION: LEAVING NO LANGUAGE BEHIND, [Paper]

• (arXiv 2022.08) Aspect-based Sentiment Classification with Sequential Cross-modal Semantic Graph, [Paper]

• (arXiv 2022.08) Diverse Video Captioning by Adaptive Spatio-temporal Attention, [Paper]

• (arXiv 2022.08) VLMAE: Vision-Language Masked Autoencoder, [Paper]

• (arXiv 2022.08) SoMoFormer: Social-Aware Motion Transformer for Multi-Person Motion Prediction, [Paper]

• (arXiv 2022.08) ILLUME: Rationalizing Vision-Language Models by Interacting with their Jabber, [Paper]

• (arXiv 2022.08) ViT-ReT: Vision and Recurrent Transformer Neural Networks for Human Activity Recognition in Videos, [Paper]

• (arXiv 2022.08) UniLayout: Taming Unified Sequence-to-Sequence Transformers for Graphic Layout Generation, [Paper]

• (arXiv 2022.08) InterTrack: Interaction Transformer for 3D Multi-Object Tracking, [Paper]

• (arXiv 2022.08) Understanding Attention for Vision-and-Language Task, [Paper]

• (arXiv 2022.08) Towards Open-vocabulary Scene Graph Generation with Prompt-based Finetuning, [Paper]

• (arXiv 2022.08) Class-Aware Visual Prompt Tuning for Vision-Language Pre-Trained Model, [Paper]

• (arXiv 2022.08) Unifying Visual Perception by Dispersible Points Learning, [Paper], [Code]

• (arXiv 2022.08) Text-to-Image Generation via Implicit Visual Guidance and Hypernetwork, [Paper]

• (arXiv 2022.08) ConMatch: Semi-Supervised Learning with Confidence-Guided Consistency Regularization, [Paper], [Code]

• (arXiv 2022.08) The 8-Point Algorithm as an Inductive Bias for Relative Pose Prediction by ViTs, [Paper]

• (arXiv 2022.08) Open-Vocabulary Panoptic Segmentation with MaskCLIP, [Paper]

• (arXiv 2022.08) Prompt Vision Transformer for Domain Generalization, [Paper]

• (arXiv 2022.08) GSRFormer: Grounded Situation Recognition Transformer with Alternate Semantic Attention Refinement, [Paper]

• (arXiv 2022.08) CONVIFORMERS: CONVOLUTIONALLY GUIDED VISION TRANSFORMER, [Paper]

• (arXiv 2022.08) Learning Spatial-Frequency Transformer for Visual Object Tracking, [Paper], [Code]

• (arXiv 2022.08) Efficient Multimodal Transformer with Dual-Level Feature Restoration for Robust Multimodal Sentiment Analysis, [Paper]

• (arXiv 2022.08) Your ViT is Secretly a Hybrid Discriminative-Generative Diffusion Model, [Paper], [Code]

• (arXiv 2022.08) LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale, [Paper]

• (arXiv 2022.08) ExpansionNet v2: Block Static Expansion in fast end to end training for Image Captioning, [Paper], [Code]

• (arXiv 2022.08) Multi-modal Transformer Path Prediction for Autonomous Vehicle, [Paper]

• (arXiv 2022.08) Flow-Guided Transformer for Video Inpainting, [Paper], [Code]

• (arXiv 2022.08) TL;DW? Summarizing Instructional Videos with Task Relevance & Cross-Modal Saliency, [Paper], [Project]

• (arXiv 2022.08) HoW-3D: Holistic 3D Wireframe Perception from a Single Image, [Paper], [Code]

• (arXiv 2022.08) BEIT V2: Masked Image Modeling with Vector-Quantized Visual Tokenizers, [Paper], [Code]

• (arXiv 2022.08) MILAN: Masked Image Pretraining on Language Assisted Representation, [Paper], [Code]

• (arXiv 2022.08) Hybrid Transformer Network for Deepfake Detection, [Paper]

• (arXiv 2022.08) Semi-supervised Vision Transformers at Scale, [Paper]

• (arXiv 2022.08) PPMN: Pixel-Phrase Matching Network for One-Stage Panoptic Narrative Grounding, [Paper], [Code]

• (arXiv 2022.08) Exploring Anchor-based Detection for Ego4D Natural Language Query, [Paper]

• (arXiv 2022.08) Language Supervised Training for Skeleton-based Action Recognition, [Paper], [Code]

• (arXiv 2022.08) Exploring Point-BEV Fusion for 3D Point Cloud Object Tracking with Transformer, [Paper], [Code]

• (arXiv 2022.08) Ghost-free High Dynamic Range Imaging with Context-aware Transformer, [Paper], [Code]

• (arXiv 2022.08) CLIP-based Neural Neighbor Style Transfer for 3D Assets, [Paper]

• (arXiv 2022.08) Sports Video Analysis on Large-Scale Data, [Paper], [Code]

• (arXiv 2022.08) How Well Do Vision Transformers (VTs) Transfer To The Non-Natural Image Domain? An Empirical Study Involving Art Classification, [Paper]

• (arXiv 2022.08) In the Eye of Transformer: Global-Local Correlation for Egocentric Gaze Estimation, [Paper], [Code]

• (arXiv 2022.08) DALLE-URBAN: Capturing the urban design expertise of large text to image transformers, [Paper], [Code]

• (arXiv 2022.08) PlaneFormers: From Sparse View Planes to 3D Reconstruction, [Paper], [Code]

• (arXiv 2022.08) Boosting Video-Text Retrieval with Explicit High-Level Semantics, [Paper]

• (arXiv 2022.08) Distinctive Image Captioning via CLIP Guided Group Optimization, [Paper]

• (arXiv 2022.08) Understanding Masked Image Modeling via Learning Occlusion Invariant Feature, [Paper]

• (arXiv 2022.08) GRIT-VLP: Grouped Mini-batch Sampling for Efficient Vision and Language Pre-training, [Paper], [Code]

• (arXiv 2022.08) Advancing Plain Vision Transformer Towards Remote Sensing Foundation Model, [Paper], [Code]

• (arXiv 2022.08) Domain Randomization-Enhanced Depth Simulation and Restoration for Perceiving and Grasping Specular and Transparent Objects, [Paper], [Code]

• (arXiv 2022.08) Jointformer: Single-Frame Lifting Transformer with Error Prediction and Refinement for 3D Human Pose Estimation, [Paper]

• (arXiv 2022.08) Frozen CLIP Models are Efficient Video Learners, [Paper], [Code]

• (arXiv 2022.08) MonoViT: Self-Supervised Monocular Depth Estimation with a Vision Transformer, [Paper], [Code]

• (arXiv 2022.08) HaloAE: An HaloNet based Local Transformer Auto-Encoder for Anomaly Detection and Localization, [Paper], [Code]

• (arXiv 2022.08) IVT: An End-to-End Instance-guided Video Transformer for 3D Pose Estimation, [Paper]

• (arXiv 2022.08) A Sketch Is Worth a Thousand Words: Image Retrieval with Text and Sketch, [Paper], [Code]

• (arXiv 2022.08) PointConvFormer: Revenge of the Point-based Convolution, [Paper]

• (arXiv 2022.08) ChiQA: A Large Scale Image-based Real-World Question Answering Dataset for Multi-Modal Understanding, [Paper]

• (arXiv 2022.08) LaTTe: Language Trajectory TransformEr, [Paper], [Code]

• (arXiv 2022.08) Learning Spatiotemporal Frequency-Transformer for Compressed Video Super-Resolution, [Paper], [Code]

• (arXiv 2022.08) TransMatting: Enhancing Transparent Objects Matting with Transformers, [Paper], [Project]

• (arXiv 2022.08) Word-Level Fine-Grained Story Visualization, [Paper]

• (arXiv 2022.08) Fine-Grained Semantically Aligned Vision-Language Pre-Training, [Paper]

• (arXiv 2022.08) Expanding Language-Image Pretrained Models for General Video Recognition, [Paper], [Code]

• (arXiv 2022.08) P2P: Tuning Pre-trained Image Models for Point Cloud Analysis with Point-to-Pixel Prompting, [Paper], [Code]

• (arXiv 2022.08) DropKey, [Paper]

• (arXiv 2022.08) MVSFormer: Multi-View Stereo with Pre-trained Vision Transformers and Temperature-based Depth, [Paper]

• (arXiv 2022.08) Per-Clip Video Object Segmentation, [Paper]

• (arXiv 2022.08) XCon: Learning with Experts for Fine-grained Category Discovery, [Paper], [Code]

• (arXiv 2022.08) Combined CNN Transformer Encoder for Enhanced Fine-grained Human Action Recognition, [Paper]

• (arXiv 2022.08) RE-ATTENTION TRANSFORMER FOR WEAKLY SUPERVISED OBJECT LOCALIZATION, [Paper], [Code]

• (arXiv 2022.08) TAG: Boosting Text-VQA via Text-aware Visual Question-answer Generation, [Paper]

• (arXiv 2022.08) Two-Stream Transformer Architecture for Long Form Video Understanding, [Paper]

• (arXiv 2022.08) A Fast Text-Driven Approach for Generating Artistic Content, [Paper]

• (arXiv 2022.08) DAHITRA: DAMAGE ASSESSMENT USING A NOVEL HIERARCHICAL TRANSFORMER ARCHITECTURE, [Paper]

• (arXiv 2022.08) MinVIS: A Minimal Video Instance Segmentation Framework without Video-based Training, [Paper], [Code]

• (arXiv 2022.08) Masked Vision and Language Modeling for Multi-modal Representation Learning, [Paper]

• (arXiv 2022.08) SSformer: A Lightweight Transformer for Semantic Segmentation, [Paper], [Code]

• (arXiv 2022.08) Pose Uncertainty Aware Movement Synchrony Estimation via Spatial-Temporal Graph Transformer, [Paper]

• (arXiv 2022.08) Making the Best of Both Worlds: A Domain-Oriented Transformer for Unsupervised Domain Adaptation, [Paper], [Code]

• (arXiv 2022.08) Unified Normalization for Accelerating and Stabilizing Transformers, [Paper]

• (arXiv 2022.08) An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion, [Paper], [Project]

• (arXiv 2022.08) Prompt-to-Prompt Image Editing with Cross Attention Control, [Paper]

• (arXiv 2022.08) Momentum Transformer: Closing the Performance Gap Between Self-attention and Its Linearization, [Paper]

• (arXiv 2022.08) Testing Relational Understanding in Text-Guided Image Generation, [Paper]

• (arXiv 2022.08) UAVM: A Unified Model for Audio-Visual Learning, [Paper]

• (arXiv 2022.08) Meta-DETR: Image-Level Few-Shot Detection with Inter-Class Correlation Exploitation, [Paper], [Code]

• (arXiv 2022.08) Point Primitive Transformer for Long-Term 4D Point Cloud Video Understanding, [Paper]

• (arXiv 2022.08) One for All: One-stage Referring Expression Comprehension with Dynamic Reasoning, [Paper]

• (arXiv 2022.08) Toward Understanding WordArt: Corner-Guided Transformer for Scene Text Recognition, [Paper], [Code]

• (arXiv 2022.08) SdAE: Self-distillated Masked Autoencoder, [Paper], [Code]

• (arXiv 2022.08) Augmenting Vision Language Pretraining by Learning Codebook with Visual Semantics, [Paper]

• (arXiv 2022.08) STrajNet: Occupancy Flow Prediction via Multi-modal Swin Transformer, [Paper]

• (arXiv 2022.08) D^3Former: Debiased Dual Distilled Transformer for Incremental Learning, [Paper], [Code]

• (arXiv 2022.08) Local Perception-Aware Transformer for Aerial Tracking, [Paper], [Code]

• (arXiv 2022.08) SIAMIXFORMER: A SIAMESE TRANSFORMER NETWORK FOR BUILDING DETECTION AND CHANGE DETECTION FROM BI-TEMPORAL REMOTE SENSING IMAGES, [Paper]

• (arXiv 2022.08) Transformers as Meta-Learners for Implicit Neural Representations, [Paper], [Code]

• (arXiv 2022.08) Video Question Answering with Iterative Video-Text Co-Tokenization, [Paper], [Code]

• (arXiv 2022.08) Understanding Adversarial Robustness of Vision Transformers via Cauchy Problem, [Paper], [Code]

2022.07

• (arXiv 2022.07) Pro-tuning: Unified Prompt Tuning for Vision Tasks, [Paper]

• (arXiv 2022.07) ALADIN: Distilling Fine-grained Alignment Scores for Efficient Image-Text Matching and Retrieval, [Paper], [Code]

• (arXiv 2022.07) Curriculum Learning for Data-Efficient Vision-Language Alignme, [Paper]

• (arXiv 2022.07) DnSwin: Toward Real-World Denoising via Continuous Wavelet Sliding-Transformer, [Paper]

• (arXiv 2022.07) Cross-Attention of Disentangled Modalities for 3D Human Mesh Recovery with Transformers, [Paper], [Code]

• (arXiv 2022.07) AvatarPoser: Articulated Full-Body Pose Tracking from Sparse Motion Sensing, [Paper], [Project]

• (arXiv 2022.07) Semantic-Aligned Matching for Enhanced DETR Convergence and Multi-Scale Feature Fusion, [Paper], [Code]

• (arXiv 2022.07) Safety-Enhanced Autonomous Driving Using Interpretable Sensor Fusion Transformer, [Paper], [Code]

• (arXiv 2022.07) Video Mask Transfiner for High-Quality Video Instance Segmentation, [Paper], [Project]

• (arXiv 2022.07) A Variational AutoEncoder for Transformers with Nonparametric Variational Information Bottleneck, [Paper]

• (arXiv 2022.07) Online Continual Learning with Contrastive Vision Transformer, [Paper]

• (arXiv 2022.07) Retrieval-Augmented Transformer for Image Captioning, [Paper]

• (arXiv 2022.07) Spatiotemporal Self-attention Modeling with Temporal Patch Shift for Action Recognition, [Paper], [Code]

• (arXiv 2022.07) Is Attention All NeRF Needs?, [Paper], [Code]

• (arXiv 2022.07) Convolutional Embedding Makes Hierarchical Vision Transformer Stronger, [Paper]

• (arXiv 2022.07) SiRi: A Simple Selective Retraining Mechanism for Transformer-based Visual Grounding, [Paper], [Code]

• (arXiv 2022.07) Deep Clustering with Features from Self-Supervised Pretraining, [Paper]

• (arXiv 2022.07) Contrastive Masked Autoencoders are Stronger Vision Learners, [Paper]

• (arXiv 2022.07) VICTOR: VISUAL INCOMPATIBILITY DETECTION WITH TRANSFORMERS AND FASHION-SPECIFIC CONTRASTIVE PRE-TRAINING, [Paper]

• (arXiv 2022.07) Compositional Human-Scene Interaction Synthesis with Semantic Control, [Paper], [Code]

• (arXiv 2022.07) Static and Dynamic Concepts for Self-supervised Video Representation Learning, [Paper]

• (arXiv 2022.07) Unsupervised Domain Adaptation for Video Transformers in Action Recognition, [Paper], [Code]

• (arXiv 2022.07) LaKo: Knowledge-driven Visual Question Answering via Late Knowledge-to-Text Injection, [Paper]

• (arXiv 2022.07) TransFiner: A Full-Scale Refinement Approach for Multiple Object Tracking, [Paper]

• (arXiv 2022.07) S-Prompts Learning with Pre-trained Transformers: An Occam’s Razor for Domain Incremental Learning, [Paper]

• (arXiv 2022.07) WinoGAViL: Gamified Association Benchmark to Challenge Vision-and-Language Models, [Paper], [Project]

• (arXiv 2022.07) Cross-Modal Causal Relational Reasoning for Event-Level Visual Question Answering, [Paper]

• (arXiv 2022.07) Graph Neural Network and Spatiotemporal Transformer Attention for 3D Video Object Detection from Point Clouds, [Paper]

• (arXiv 2022.07) Learning Visual Representation from Modality-Shared Contrastive Language-Image Pre-training, [Paper], [Code]

• (arXiv 2022.07) V^2L: Leveraging Vision and Vision-language Models into Large-scale Product Retrieval, [Paper], [Code]

• (arXiv 2022.07) NewsStories: Illustrating articles with visual summaries, [Paper], [Project]

• (arXiv 2022.07) DETRs with Hybrid Matching, [Paper], [Code]

• (arXiv 2022.07) GROUP DETR: FAST TRAINING CONVERGENCE WITH DECOUPLED ONE-TO-MANY LABEL ASSIGNMENT, [Paper]

• (arXiv 2022.07) Improved Super Resolution of MR Images Using CNNs and Vision Transformers, [Paper]

• (arXiv 2022.07) Video Swin Transformers for Egocentric Video Understanding @ Ego4D Challenges 2022, [Paper], [Code]

• (arXiv 2022.07) An Impartial Take to the CNN vs Transformer Robustness Contest, [Paper]

• (arXiv 2022.07) Generative Artisan: A Semantic-Aware and Controllable CLIPstyler, [Paper]

• (arXiv 2022.07) MAR: Masked Autoencoders for Efficient Action Recognition, [Paper], [Code]

• (arXiv 2022.07) Object State Change Classification in Egocentric Videos using the Divided Space-Time Attention Mechanism, [Paper], [Cpde]

• (arXiv 2022.07) Behind Every Domain There is a Shift: Adapting Distortion-aware Vision Transformers for Panoramic Semantic Segmentation, [Paper], [Code]

• (arXiv 2022.07) Reference-based Image Super-Resolution with Deformable Attention Transformer, [Paper], [Code]

• (arXiv 2022.07) JIGSAW-VIT: LEARNING JIGSAW PUZZLES IN VISION TRANSFORMER, [Paper], [Code]

• (arXiv 2022.07) TransCL: Transformer Makes Strong and Flexible Compressive Learning, [Paper], [Code]

• (arXiv 2022.07) 3D Siamese Transformer Network for Single Object Tracking on Point Clouds, [Paper], [Code]

• (arXiv 2022.07) Intention-Conditioned Long-Term Human Egocentric Action Forecasting @ EGO4D Challenge 2022, [Paper], [Code]

• (arXiv 2022.07) IGFormer: Interaction Graph Transformer for Skeleton-based Human Interaction Recognition, [Paper]

• (arXiv 2022.07) Is GPT-3 all you need for Visual Question Answering in Cultural Heritage? [Paper]

• (arXiv 2022.07) Applying Spatiotemporal Attention to Identify Distracted and Drowsy Driving with Vision Transformers, [Paper]

• (arXiv 2022.07) Action Quality Assessment using Transformers, [Paper]

• (arXiv 2022.07) Self-Distilled Vision Transformer for Domain Generalization, [Paper], [Code]

• (arXiv 2022.07) Exploring CLIP for Assessing the Look and Feel of Images, [Paper], [Code]

• (arXiv 2022.07) Transformer with Implicit Edges for Particle-based Physics Simulation, [Paper], [Code]

• (arXiv 2022.07) Auto-regressive Image Synthesis with Integrated Quantization, [Paper]

• (arXiv 2022.07) Efficient Modeling of Future Context for Image Captioning, [Paper], [Code]

• (arXiv 2022.07) Zero-Shot Video Captioning with Evolving Pseudo-Tokens, [Paper], [Code]

• (arXiv 2022.07) Panoptic Scene Graph Generation, [Paper], [Project], [Code]

• (arXiv 2022.07) Facial Expression Recognition using Vanilla ViT backbones with MAE Pretraining, [Paper]

• (arXiv 2022.07) Target-Driven Structured Transformer Planner for Vision-Language Navigation, [Paper]

• (arXiv 2022.07) Scaling Laws vs Model Architectures: How does Inductive Bias Influence Scaling? [Paper]

• (arXiv 2022.07) Hybrid CNN-Transformer Model For Facial Affect Recognition In the ABAW4 Challenge, [Paper]

• (arXiv 2022.07) MeshMAE: Masked Autoencoders for 3D Mesh Data Analysis, [Paper]

• (arXiv 2022.07) SeedFormer: Patch Seeds based Point Cloud Completion with Upsample Transformer, [Paper], [Code]

• (arXiv 2022.07) LocVTP: Video-Text Pre-training for Temporal Localization, [Paper], [Code]

• (arXiv 2022.07) Temporal Saliency Query Network for Efficient Video Recognition, [Paper], [Code]

• (arXiv 2022.07) Pose for Everything: Towards Category-Agnostic Pose Estimation, [Paper], [Code]

• (arXiv 2022.07) Weakly Supervised Object Localization via Transformer with Implicit Spatial Calibration, [Paper], [Code]

• (arXiv 2022.07) An Efficient Spatio-Temporal Pyramid Transformer for Action Detection, [Paper]

• (arXiv 2022.07) Towards Efficient Adversarial Training on Vision Transformers, [Paper]

• (arXiv 2022.07) TinyViT: Fast Pretraining Distillation for Small Vision Transformers, [Paper], [Code]

• (arXiv 2022.07) Hierarchically Self-Supervised Transformer for Human Skeleton Representation Learning, [Paper], [Code]

• (arXiv 2022.07) Explicit Image Caption Editing, [Paper], [Code]

• (arXiv 2022.07) AiATrack: Attention in Attention for Transformer Visual Tracking, [Paper], [Code]

• (arXiv 2022.07) Tip-Adapter: Training-free Adaption of CLIP for Few-shot Classification, [Paper], [Code]

• (arXiv 2022.07) Single Frame Atmospheric Turbulence Mitigation: A Benchmark Study and A New Physics-Inspired Transformer Model, [Paper], [Code]

• (arXiv 2022.07) HTNet: Anchor-free Temporal Action Localization with Hierarchical Transformers, [Paper]

• (arXiv 2022.07) GRIT: Faster and Better Image captioning Transformer Using Dual Visual Features, [Paper]

• (arXiv 2022.07) OTPose: Occlusion-Aware Transformer for Pose Estimation in Sparsely-Labeled Videos, [Paper]

• (arXiv 2022.07) FaceFormer: Scale-aware Blind Face Restoration with Transformers, [Paper]

• (arXiv 2022.07) Multimodal Transformer for Automatic 3D Annotation and Object Detection, [Paper], [Code]

• (arXiv 2022.07) Temporal and cross-modal attention for audio-visual zero-shot learning, [Paper], [Code]

• (arXiv 2022.07) Locality Guidance for Improving Vision Transformers on Tiny Datasets, [Paper], [Code]

• (arXiv 2022.07) Is an Object-Centric Video Representation Beneficial for Transfer? [Paper]

• (arXiv 2022.07) DUQIM-Net: Probabilistic Object Hierarchy Representation for Multi-View Manipulation, [Paper]

• (arXiv 2022.07) RELATIONAL FUTURE CAPTIONING MODEL FOR EXPLAINING LIKELY COLLISIONS IN DAILY TASKS, [Paper]

• (arXiv 2022.07) Conditional DETR V2: Efficient Detection Transformer with Box Queries, [Paper]

• (arXiv 2022.07) Exploiting Unlabeled Data with Vision and Language Models for Object Detection, [Paper], [Code]

• (arXiv 2022.07) TTVFI: Learning Trajectory-Aware Transformer for Video Frame Interpolation, [Paper], [Code]

• (arXiv 2022.07) Time Is MattEr: Temporal Self-supervision for Video Transformers, [Paper]

• (arXiv 2022.07) IDET: Iterative Difference-Enhanced Transformers for High-Quality Change Detection, [Paper]

• (arXiv 2022.07) Don’t Stop Learning: Towards Continual Learning for the CLIP Model, [Paper]

• (arXiv 2022.07) Action Quality Assessment with Temporal Parsing Transformer, [Paper]

• (arXiv 2022.07) Visual Representation Learning with Transformer: A Sequence-to-Sequence Perspective, [Paper], [Code]

• (arXiv 2022.07) Structural Prior Guided Generative Adversarial Transformers for Low-Light Image Enhancement, [Paper]

• (arXiv 2022.07) TS2-Net: Token Shift and Selection Transformer for Text-Video Retrieval, [Paper], [Code]

• (arXiv 2022.07) Clover: Towards A Unified Video-Language Alignment and Fusion Model, [Paper], [Code]

• (arXiv 2022.07) SatMAE: Pre-training Transformers for Temporal and Multi-Spectral Satellite Imagery, [Paper]

• (arXiv 2022.07) FashionViL: Fashion-Focused Vision-and-Language Representation Learning, [Paper], [Code]

• (arXiv 2022.07) Zero-Shot Temporal Action Detection via Vision-Language Prompting, [Paper], [Code]

• (arXiv 2022.07) Rethinking Alignment in Video Super-Resolution Transformers, [Paper], [Code]

• (arXiv 2022.07) Open-world Semantic Segmentation via Contrasting and Clustering Vision-Language Embedding, [Paper]

• (arXiv 2022.07) TokenMix: Rethinking Image Mixing for Data Augmentation in Vision Transformers, [Paper], [Code]

• (arXiv 2022.07) Towards the Human Global Context: Does the Vision-Language Model Really Judge Like a Human Being? [Paper]

• (arXiv 2022.07) Defect Transformer: An Efficient Hybrid Transformer Architecture for Surface Defect Detection, [Paper]

• (arXiv 2022.07) Semantic Novelty Detection via Relational Reasoning, [Paper]

• (arXiv 2022.07) Unifying Event Detection and Captioning as Sequence Generation via Pre-Training, [Paper], [Code]

• (arXiv 2022.07) Multi-manifold Attention for Vision Transformers, [Paper]

• (arXiv 2022.07) UniFormer: Unified Multi-view Fusion Transformer for Spatial-Temporal Representation in Bird’s-Eye-View, [Paper]

• (arXiv 2022.07) Position Prediction as an Effective Pretraining Strategy, [Paper]

• (arXiv 2022.07) Lightweight Vision Transformer with Cross Feature Attention, [Paper]

• (arXiv 2022.07) Parameterization of Cross-Token Relations with Relative Positional Encoding for Vision MLP, [Paper], [Code]

• (arXiv 2022.07) X-CLIP: End-to-End Multi-grained Contrastive Learning for Video-Text Retrieval, [Paper]

• (arXiv 2022.07) Learning Parallax Transformer Network for Stereo Image JPEG Artifacts Removal, [Paper]

• (arXiv 2022.07) A Dual-Masked Auto-Encoder for Robust Motion Capture with Spatial-Temporal Skeletal Token Completion, [Paper]

• (arXiv 2022.07) Is a Caption Worth a Thousand Images? A Controlled Study for Representation Learning, [Paper]

• (arXiv 2022.07) Multimodal Open-Vocabulary Video Classification via Pre-Trained Vision and Language Models, [Paper]

• (arXiv 2022.07) Cross-Attention Transformer for Video Interpolation, [Paper]

• (arXiv 2022.07) Towards Multimodal Vision-Language Models Generating Non-Generic Text, [Paper]

• (arXiv 2022.07) QKVA grid: Attention in Image Perspective and Stacked DETR, [Paper], [Code]

• (arXiv 2022.07) Snipper: A Spatiotemporal Transformer for Simultaneous Multi-Person 3D Pose Estimation Tracking and Forecasting on a Video Snippet, [Paper], [Code]

• (arXiv 2022.07) Horizontal and Vertical Attention in Transformers, [Paper]

• (arXiv 2022.07) CoMER: Modeling Coverage for Transformer-based Handwritten Mathematical Expression Recognition, [Paper], [Code]

• (arXiv 2022.07) DPText-DETR: Towards Better Scene Text Detection with Dynamic Points in Transformer, [Paper], [Code]

• (arXiv 2022.07) DEPTHFORMER: MULTISCALE VISION TRANSFORMER FOR MONOCULAR DEPTH ESTIMATION WITH GLOBAL LOCAL INFORMATION FUSION, [Paper], [Code]

• (arXiv 2022.07) LaT: Latent Translation with Cycle-Consistency for Video-Text Retrieval, [Paper]

• (arXiv 2022.07) Dual Vision Transformer, [Paper], [Code]

• (arXiv 2022.07) Wave-ViT: Unifying Wavelet and Transformers for Visual Representation Learning, [Paper], [Code]

• (arXiv 2022.07) Scaling Novel Object Detection with Weakly Supervised Detection Transformers, [Paper]

• (arXiv 2022.07) Hunting Group Clues with Transformers for Social Group Activity Recognition, [Paper]

• (arXiv 2022.07) Outpainting by Queries, [Paper], [Code]

• (arXiv 2022.07) IDEA: Increasing Text Diversity via Online Multi-Label Recognition for Vision-Language Pre-training, [Paper]

• (arXiv 2022.07) Video Graph Transformer for Video Question Answering, [Paper], [Code]

• (arXiv 2022.07) Next-ViT: Next Generation Vision Transformer for Efficient Deployment in Realistic Industrial Scenarios, [Paper]

• (arXiv 2022.07) UniNet: Unified Architecture Search with Convolution, Transformer, and MLP, [Paper], [Code]

• (arXiv 2022.07) Image and Model Transformation with Secret Key for Vision Transformer, [Paper]

• (arXiv 2022.07) eX-ViT: A Novel eXplainable Vision Transformer for Weakly Supervised Semantic Segmentation, [Paper]

• (arXiv 2022.07) Compound Prototype Matching for Few-shot Action Recognition, [Paper]

• (arXiv 2022.07) Long-term Leap Attention, Short-term Periodic Shift for Video Classification, [Paper], [Code]

• (arXiv 2022.07) LightViT: Towards Light-Weight Convolution-Free Vision Transformers, [Paper], [Code]

• (arXiv 2022.07) Learning from Label Relationships in Human Affect, [Paper]

• (arXiv 2022.07) MSP-Former: Multi-Scale Projection Transformer for Single Image Desnowing, [Paper]

• (arXiv 2022.07) Tell Me the Evidence? Dual Visual-Linguistic Interaction for Answer Grounding, [Paper]

• (arXiv 2022.07) Vision Transformer for NeRF-Based View Synthesis from a Single Input Image, [Paper], [Code]

• (arXiv 2022.07) COSIM: Commonsense Reasoning for Counterfactual Scene Imagination, [Paper], [Code]

• (arXiv 2022.07) Beyond Transfer Learning: Co-finetuning for Action Localisation, [Paper]

• (arXiv 2022.07) RePFormer: Refinement Pyramid Transformer for Robust Facial Landmark Detection, [Paper]

• (arXiv 2022.07) k-means Mask Transformer, [Paper], [Code]

• (arXiv 2022.07) Training Transformers Together, [Paper], [Code]

• (arXiv 2022.07) Improving Few-Shot Image Classification Using Machine- and User-Generated Natural Language Descriptions, [Paper]

• (arXiv 2022.07) MaiT: Leverage Attention Masks for More Efficient Image Transformers, [Paper]

• (arXiv 2022.07) Dual-Stream Transformer for Generic Event Boundary Captioning, [Paper], [Code]

• (arXiv 2022.07) Softmax-free Linear Transformers, [Paper], [[Code[[(https://github.com/fudan-zvg/SOFT)

• (arXiv 2022.07) Bridging the Gap between Object and Image-level Representations for Open-Vocabulary Detection, [Paper], [Code]

• (arXiv 2022.07) Transformers are Adaptable Task Planners, [Paper], [Code]

• (arXiv 2022.07) ARRAY CAMERA IMAGE FUSION USING PHYSICS-AWARE TRANSFORMERS, [Paper]

• (arXiv 2022.07) OSFormer: One-Stage Camouflaged Instance Segmentation with Transformers, [Paper], [Code]

• (arXiv 2022.07) Weakly Supervised Grounding for VQA in Vision-Language Transformers, [Paper], [Code]

• (arXiv 2022.07) PIC 4th Challenge: Semantic-Assisted Multi-Feature Encoding and Multi-Head Decoding for Dense Video Captioning, [Paper]

• (arXiv 2022.07) STVGFormer: Spatio-Temporal Video Grounding with Static-Dynamic Cross-Modal Understanding, [Paper]

• (arXiv 2022.07) Towards Counterfactual Image Manipulation via CLIP, [Paper]

• (arXiv 2022.07) MatFormer: A Generative Model for Procedural Materials, [Paper]

• (arXiv 2022.07) Multimodal Frame-Scoring Transformer for Video Summarization, [Paper]

• (arXiv 2022.07) 3D Part Assembly Generation with Instance Encoded Transformer, [Paper]

• (arXiv 2022.07) Scene-Aware Prompt for Multi-modal Dialogue Understanding and Generation, [Paper]

• (arXiv 2022.07) Efficient Representation Learning via Adaptive Context Pooling, [Paper]

• (arXiv 2022.07) Gaze Target Estimation inspired by Interactive Attention, [Paper], [Code]

• (arXiv 2022.07) Generalizable Patch-Based Neural Rendering, [Paper], [Project]

• (arXiv 2022.07) Interaction Transformer for Human Reaction Generation, [Paper]

• (arXiv 2022.07) TM2T: Stochastic and Tokenized Modeling for the Reciprocal Generation of 3D Human Motions and Texts, [Paper], [Project]

• (arXiv 2022.07) FishFormer: Annulus Slicing-based Transformer for Fisheye Rectification with Efficacy Domain Exploration, [Paper]

• (arXiv 2022.07) Open-Vocabulary Multi-Label Classification via Multi-modal Knowledge Transfer, [Paper], [Code]

• (arXiv 2022.07) Toward Explainable and Fine-Grained 3D Grounding through Referring Textual Phrases, [Paper], [Code]

• (arXiv 2022.07) Improving Semantic Segmentation in Transformers using Hierarchical Inter-Level Attention, [Paper]

• (arXiv 2022.07) MULTI-MODAL ROBUSTNESS ANALYSIS AGAINST LANGUAGE AND VISUAL PERTURBATIONS, [Paper], [Project]

• (arXiv 2022.07) CoBEVT: Cooperative Bird’s Eye View Semantic Segmentation with Sparse Transformers, [Paper]

• (arXiv 2022.07) Segmenting Moving Objects via an Object-Centric Layered Representation, [Paper]

• (arXiv 2022.07) Counterfactually Measuring and Eliminating Social Bias in Vision-Language Pre-training Models, [Paper]

• (arXiv 2022.07) Contrastive Cross-Modal Knowledge Sharing Pre-training for Vision-Language Representation Learning and Retrieval, [Paper]

• (arXiv 2022.07) Learning Cross-Image Object Semantic Relation in Transformer for Few-Shot Fine-Grained Image Classification, [Paper], [Code]

• (arXiv 2022.07) Memory-Based Label-Text Tuning for Few-Shot Class-Incremental Learning, [Paper]

• (arXiv 2022.07) Exploiting Context Information for Generic Event Boundary Captioning, [Paper], [Code]

• (arXiv 2022.07) You Only Need One Detector: Unified Object Detector for Different Modalities based on Vision Transformers, [Paper], [Code]

• (arXiv 2022.07) Divert More Attention to Vision-Language Tracking, [Paper], [Code]

• (arXiv 2022.07) Can Language Understand Depth? [Paper], [Code]

• (arXiv 2022.07) TANet: Transformer-based Asymmetric Network for RGB-D Salient Object Detection, [Paper], [Code]

• (arXiv 2022.07) DUET: Cross-modal Semantic Grounding for Contrastive Zero-shot Learning, [Paper]

• (arXiv 2022.07) Transferring Textual Knowledge for Visual Recognition, [Paper], [Code]

• (arXiv 2022.07) R^2-VOS: Robust Referring Video Object Segmentation via Relational Cycle Consistency, [Paper]

• (arXiv 2022.07) CRFormer: A Cross-Region Transformer for Shadow Removal, [Paper]

• (arXiv 2022.07) Dynamic Spatial Sparsification for Efficient Vision Transformers and Convolutional Neural Networks, [Paper], [Code]

• (arXiv 2022.07) Back to MLP: A Simple Baseline for Human Motion Prediction, [Paper], [Code]

• (arXiv 2022.07) I-ViT: Integer-only Quantization for Efficient Vision Transformer Inference, [Paper]

• (arXiv 2022.07) Rethinking Query-Key Pairwise Interactions in Vision Transformers, [Paper]

• (arXiv 2022.07) LARGE-SCALE ROBUSTNESS ANALYSIS OF VIDEO ACTION RECOGNITION MODELS, [Paper], [Code]

• (arXiv 2022.07) VL-CheckList: Evaluating Pre-trained Vision-Language Models with Objects, Attributes and Relations, [Paper], [Code]

• (arXiv 2022.07) Masked Autoencoders for Self-Supervised Learning on Automotive Point Clouds, [Paper]

• (arXiv 2022.07) MotionMixer: MLP-based 3D Human Body Pose Forecasting, [Paper], [Code]

• (arXiv 2022.07) DALG: Deep Attentive Local and Global Modeling for Image Retrieval, [Paper]

• (arXiv 2022.07) PolarFormer: Multi-camera 3D Object Detection with Polar Transformers, [Paper], [Code]

• (arXiv 2022.07) CTrGAN: Cycle Transformers GAN for Gait Transfer, [Paper]

• (arXiv 2022.07) LM-Nav: Robotic Navigation with Large Pre-Trained Models of Language, Vision, and Action, [Paper]

• (arXiv 2022.07) Bootstrapped Masked Autoencoders for Vision BERT Pretraining, [Paper], [Code]

• (arXiv 2022.07) ReAct: Temporal Action Detection with Relational Queries, [Paper], [Code]

• (arXiv 2022.07) Benchmarking Omni-Vision Representation through the Lens of Visual Realms, [Paper], [Project]

• (arXiv 2022.07) Convolutional Bypasses Are Better Vision Transformer Adapters, [Paper]

• (arXiv 2022.07) LANGUAGE MODELLING WITH PIXELS, [Paper]

• (arXiv 2022.07) Transformer-based Context Condensation for Boosting Feature Pyramids in Object Detection, [Paper]

• (arXiv 2022.07) DEEPFAKE VIDEO DETECTION WITH SPATIOTEMPORAL DROPOUT TRANSFORMER, [Paper]

• (arXiv 2022.07) iColoriT: Towards Propagating Local Hint to the Right Region in Interactive Colorization by Leveraging Vision Transformer, [Paper]

• (arXiv 2022.07) Imaging through the Atmosphere using Turbulence Mitigation Transformer, [Paper]

• (arXiv 2022.07) Symmetry-Aware Transformer-based Mirror Detection, [Paper], [Code]

• (arXiv 2022.07) Pyramid Transformer for Traffic Sign Detection, [Paper]

• (arXiv 2022.07) Global-local Motion Transformer for Unsupervised Skeleton-based Action Learning, [Paper], [Code]

• (arXiv 2022.07) DynaST: Dynamic Sparse Transformer for Exemplar-Guided Image Generation, [Paper]

• (arXiv 2022.07) Trans4Map: Revisiting Holistic Top-down Mapping from Egocentric Images to Allocentric Semantics with Vision Transformers, [Paper], [Code]

• (arXiv 2022.07) Entry-Flipped Transformer for Inference and Prediction of Participant Behavior, [Paper]

• (arXiv 2022.07) Wayformer: Motion Forecasting via Simple & Efficient Attention Networks, [Paper]

• (arXiv 2022.07) Diverse Dance Synthesis via Keyframes with Transformer Controllers, [Paper]

• (arXiv 2022.07) Learning to Estimate External Forces of Human Motion in Video, [Paper]

• (arXiv 2022.07) Vision Transformer for Contrastive Clustering, [Paper], [Code]

• (arXiv 2022.07) Pose2Room: Understanding 3D Scenes from Human Activities, [Paper]

• (arXiv 2022.07) Towards Hard-Positive Query Mining for DETR-based Human-Object Interaction Detection, [Paper], [Code]

• (arXiv 2022.07) Cross-Architecture Knowledge Distillation, [Paper]

• (arXiv 2022.07) Distance Matters in Human-Object Interaction Detection, [Paper]

2022.06

• (arXiv 2022.06) TENET: Transformer Encoding Network for Effective Temporal Flow on Motion Prediction, [Paper]

• (arXiv 2022.06) GaitForeMer: Self-Supervised Pre-Training of Transformers via Human Motion Forecasting for Few-Shot Gait Impairment Severity Estimation, [Paper], [Code]

• (arXiv 2022.06) GSCLIP : A Framework for Explaining Distribution Shifts in Natural Language, [Paper]

• (arXiv 2022.06) Spatial Transformer Network with Transfer Learning for Small-scale Fine-grained Skeleton-based Tai Chi Action Recognition, [Paper]

• (arXiv 2022.06) Causality for Inherently Explainable Transformers: CAT-XPLAIN, [Paper], [Code]

• (arXiv 2022.06) A Unified End-to-End Retriever-Reader Framework for Knowledge-based VQA, [Paper]

• (arXiv 2022.06) Continual Learning with Transformers for Image Classification, [Paper]

• (arXiv 2022.06) ST-Adapter: Parameter-Efficient Image-to-Video Transfer Learning for Action Recognition, [Paper]

• (arXiv 2022.06) Robustifying Vision Transformer without Retraining from Scratch by Test-Time Class-Conditional Feature Alignment, [Paper], [Code]

• (arXiv 2022.06) Leveraging Language for Accelerated Learning of Tool Manipulation, [Paper]

• (arXiv 2022.06) RoME: Role-aware Mixture-of-Expert Transformer for Text-to-Video Retrieval, [Paper]

• (arXiv 2022.06) VLCAP: VISION-LANGUAGE WITH CONTRASTIVE LEARNING FOR COHERENT VIDEO PARAGRAPH CAPTIONING, [Paper], [Code]

• (arXiv 2022.06) Video2StyleGAN: Encoding Video in Latent Space for Manipulation, [Paper]

• (arXiv 2022.06) Text-Driven Stylization of Video Objects, [Paper], [Project]

• (arXiv 2022.06) Open Vocabulary Object Detection with Proposal Mining and Prediction Equalization, [Paper], [Code]

• (arXiv 2022.06) CMT-DeepLab: Clustering Mask Transformers for Panoptic Segmentation, [Paper]

• (arXiv 2022.06) Towards Adversarial Attack on Vision-Language Pre-training Models, [Paper]

• (arXiv 2022.06) CLiMB: A Continual Learning Benchmark for Vision-and-Language Tasks, [Paper], [Code]

• (arXiv 2022.06) VISUALIZING AND UNDERSTANDING SELF-SUPERVISED VISION LEARNING, [Paper], [Code]

• (arXiv 2022.06) VReBERT: A Simple and Flexible Transformer for Visual Relationship Detection, [Paper]

• (arXiv 2022.06) Bear the Query in Mind: Visual Grounding with Query-conditioned Convolution, [Paper]

• (arXiv 2022.06) DALL-E for Detection: Language-driven Context Image Synthesis for Object Detection, [Paper]

• (arXiv 2022.06) REVECA – Rich Encoder-decoder framework for Video Event CAptioner, [Paper], [Code]

• (arXiv 2022.06) SAViR-T: Spatially Attentive** Visual Reasoning** with Transformers, [Paper]

• (arXiv 2022.06) EATFormer: Improving Vision Transformer Inspired by Evolutionary Algorithm, [Paper], [Code]

• (arXiv 2022.06) DualCoOp: Fast Adaptation to Multi-Label Recognition with Limited Annotations, [Paper]

• (arXiv 2022.06) Capturing and Inferring Dense Full-Body Human-Scene Contact, [Paper], [Project]

• (arXiv 2022.06) M&M Mix: A Multimodal Multiview Transformer Ensemble, [Paper]

• (arXiv 2022.06) DisCoVQA: Temporal Distortion-Content Transformers for Video Quality Assessment, [Paper]

• (arXiv 2022.06) Voxel-MAE: Masked Autoencoders for Pre-training Large-scale Point Clouds, [Paper], [Code]

• (arXiv 2022.06) Global Context Vision Transformers, [Paper], [Code]

• (arXiv 2022.06) Counting Varying Density Crowds Through Density Guided Adaptive Selection CNN and Transformer Estimation, [Paper]

• (arXiv 2022.06) One-stage Action Detection Transformer, [Paper]

• (arXiv 2022.06) SemMAE: Semantic-Guided Masking for Learning Masked Autoencoders, [Paper]

• (arXiv 2022.06) TRANSFORMER-BASED MULTI-MODAL PROPOSAL AND RE-RANK FOR WIKIPEDIA IMAGE-CAPTION MATCHING, [Paper], [Code]

• (arXiv 2022.06) Vicinity Vision Transformer, [Paper], [Code]

• (arXiv 2022.06) EdgeNeXt: Efficiently Amalgamated CNN-Transformer Architecture for Mobile Vision Applications, [Paper], [Code]

• (arXiv 2022.06) Temporally Consistent Semantic Video Editing, [Paper]

• (arXiv 2022.06) VLMbench: A Compositional Benchmark for Vision-and-Language Manipulation, [Paper]

• (arXiv 2022.06) MINEDOJO: Building Open-Ended Embodied Agents with Internet-Scale Knowledge, [Paper], [Project]

• (arXiv 2022.06) IRISformer: Dense Vision Transformers for Single-Image Inverse Rendering in Indoor Scenes, [Paper], [Code]

• (arXiv 2022.06) Backdoor Attacks on Vision Transformers, [Paper], [Code]

• (arXiv 2022.06) Rectify ViT Shortcut Learning by Visual Saliency, [Paper]

• (arXiv 2022.06) Learning Using Privileged Information for Zero-Shot Action Recognition, [Paper]

• (arXiv 2022.06) Bridge-Tower: Building Bridges Between Encoders in Vision-Language Representation Learning, [Paper], [Code]

• (arXiv 2022.06) CtrlFormer: Learning Transferable State Representation for Visual Control via Transformer, [Paper], [Project]

• (arXiv 2022.06) SimA: Simple Softmax-free Attention for Vision Transformers, [Paper], [Code]

• (arXiv 2022.06) UNIFIED-IO: A UNIFIED MODEL FOR VISION, LANGUAGE, AND MULTI-MODAL TASKS, [Paper], [Project]

• (arXiv 2022.06) VLMixer: Unpaired Vision-Language Pre-training via Cross-Modal CutMix, [Paper], [Code]

• (arXiv 2022.06) ReLER@ZJU-Alibaba Submission to the Ego4D Natural Language Queries Challenge 2022, [Paper]

• (arXiv 2022.06) Video + CLIP Baseline for Ego4D Long-term Action Anticipation, [Paper], [Code]

• (arXiv 2022.06) What makes domain generalization hard?, [Paper]

• (arXiv 2022.06) SAVi++: Towards End-to-End Object-Centric Learning from Real-World Videos, [Paper], [Code]

• (arXiv 2022.06) Disentangling visual and written concepts in CLIP, [Paper], [Project]

• (arXiv 2022.06) Multi-scale Cooperative Multimodal Transformers for Multimodal Sentiment Analysis in Videos, [Paper]

• (arXiv 2022.06) Patch-level Representation Learning for Self-supervised Vision Transformers, [Paper]

• (arXiv 2022.06) Zero-Shot Video Question Answering via Frozen Bidirectional Language Models, [Paper], [Code]

• (arXiv 2022.06) OmniMAE: Single Model Masked Pretraining on Images and Videos, [Paper], [Code]

• (arXiv 2022.06) Adapting Self-Supervised Vision Transformers by Probing Attention-Conditioned Masking Consistency, [Paper], [Code]

• (arXiv 2022.06) LAVENDER: Unifying Video-Language Understanding as Masked Language Modeling, [Paper], [Code]

• (arXiv 2022.06) Multimodal Event Graphs: Towards Event Centric Understanding of Multimodal World, [Paper]

• (arXiv 2022.06) Rethinking Generalization in Few-Shot Classification, [Paper], [Code]

• (arXiv 2022.06) VCT: A Video Compression Transformer, [Paper]

• (arXiv 2022.06) Forecasting of depth and ego-motion with transformers and self-supervision, [Paper]

• (arXiv 2022.06) Coarse-to-Fine Vision-Language Pre-training with Fusion in the Backbone, [Paper], [Code]

• (arXiv 2022.06) SP-ViT: Learning 2D Spatial Priors for Vision Transformers, [Paper]

• (arXiv 2022.06) A Simple Data Mixing Prior for Improving Self-Supervised Learning, [Paper], [Code]

• (arXiv 2022.06) Prefix Language Models are Unified Modal Learners, [Paper], [Code]

• (arXiv 2022.06) Masked Frequency Modeling for Self-Supervised Visual Pre-Training, [Paper], [Code]](https://www.mmlab-ntu.com/project/mfm/index.html)

• (arXiv 2022.06) Generalizable Neural Radiance Fields for Novel View Synthesis with Transformer, [Paper]

• (arXiv 2022.06) A Unified Continuous Learning Framework for Multi-modal Knowledge Discovery and Pre-training, [Paper]

• (arXiv 2022.06) Learning to Estimate Shapley Values with Vision Transformers, [Paper], [Code]

• (arXiv 2022.06) Graph-based Spatial Transformer with Memory Replay for Multi-future Pedestrian Trajectory Prediction, [Paper], [Code]

• (arXiv 2022.06) GLIPv2: Unifying Localization and VL Understanding, [Paper], [Code]

• (arXiv 2022.06) INDIGO: Intrinsic Multimodality for Domain Generalization, [Paper]

• (arXiv 2022.06) TRANSDUCTIVE CLIP WITH CLASS-CONDITIONAL CONTRASTIVE LEARNING, [Paper]

• (arXiv 2022.06) SILVER-BULLET-3D AT MANISKILL 2021: LEARNING-FROM-DEMONSTRATIONS AND HEURISTIC RULE-BASED METHODS FOR OBJECT MANIPULATION, [Paper], [Code]

• (arXiv 2022.06) MLP-3D: A MLP-like 3D Architecture with Grouped Time Mixing, [Paper], [Code]

• (arXiv 2022.06) Visual Transformer for Object Detection, [Paper]

• (arXiv 2022.06) Bringing **Image Scene Structure to Video via Frame-Clip Consistency of Object Tokens, [Paper], [Code]

• (arXiv 2022.06) TransVG++: End-to-End Visual Grounding with Language Conditioned Vision Transformer, [Paper]

• (arXiv 2022.06) ReCo: Retrieve and Co-segment for Zero-shot Transfer, [Paper], [Project]

• (arXiv 2022.06) MAREO: MEMORY- AND ATTENTION- BASED VISUAL REASONING, [Paper]

• (arXiv 2022.06) Recurrent Transformer Variational Autoencoders for Multi-Action Motion Synthesis, [Paper]

• (arXiv 2022.06) Object Scene Representation Transformer, [Paper]

• (arXiv 2022.06) Comprehending and Ordering Semantics for Image Captioning, [Paper], [Code]

• (arXiv 2022.06) Exploring Adversarial Attacks and Defenses in Vision Transformers trained with DINO, [Paper]

• (arXiv 2022.06) Peripheral Vision Transformer, [Paper], [Code]

• (arXiv 2022.06) Efficient Decoder-free Object Detection with Transformers, [Paper], [Code]

• (arXiv 2022.06) Prototypical Contrastive Language Image Pretraining, [Paper], [Code]

• (arXiv 2022.06) SpA-Former:Transformer image** shadow detection and removal** via spatial attention, [Paper], [Code]

• (arXiv 2022.06) A Unified and Biologically-Plausible Relational Graph Representation of Vision Transformers, [Paper]

• (arXiv 2022.06) Can Foundation Models Talk Causality? [Paper]

• (arXiv 2022.06) Learning Viewpoint-Agnostic Visual Representations by Recovering Tokens in 3D Space, [Paper], [Code]

• (arXiv 2022.06) MaskViT: Masked Visual Pre-Training for Video Prediction, [Paper]

• (arXiv 2022.06) PromptPose: Language Prompt Helps Animal Pose Estimation, [Paper]

• (arXiv 2022.06) Video PreTraining (VPT): Learning to Act by Watching Unlabeled Online Videos, [Paper]

• (arXiv 2022.06) MERLOT Reserve: Neural Script Knowledge through Vision and Language and Sound, [Paper], [Project]

• (arXiv 2022.06) Building Spatio-temporal Transformers for Egocentric 3D Pose Estimation, [Paper]

• (arXiv 2022.06) Position Labels for Self-Supervised Vision Transformer, [Paper]

• (arXiv 2022.06) Exploring Feature Self-relation for Self-supervised Transformer, [Paper]

• (arXiv 2022.06) Patch-based Object-centric Transformers for Efficient Video Generation, [Paper], [Code]

• (arXiv 2022.06) Sparse Fusion Mixture-of-Experts are Domain Generalizable Learners, [Paper], [Code]

• (arXiv 2022.06) VN-Transformer: Rotation-Equivariant Attention for Vector Neurons, [Paper]

• (arXiv 2022.06) CLIP-Actor: Text-Driven Recommendation and Stylization for Animating Human Meshes, [Paper], [Code]

• (arXiv 2022.06) OOD Augmentation May Be at Odds with Open-Set Recognition, [Paper]

• (arXiv 2022.06) Draft-and-Revise: Effective Image Generation with Contextual RQ-Transformer, [Paper]

• (arXiv 2022.06) cycle text2face: cycle text-to-face gan via transformers, [Paper]

• (arXiv 2022.06) Efficient and Robust 2D-to-BEV Representation Learning via Geometry-guided Kernel Transformer, [Paper], [Code]

• (arXiv 2022.06) Transformer based Urdu Handwritten Text Optical Character Reader, [Paper]

• (arXiv 2022.06) Spatial Entropy Regularization for Vision Transformers, [Paper]

• (arXiv 2022.06) On Data Scaling in Masked Image Modeling, [Paper]

• (arXiv 2022.06) Extreme Masking for Learning Instance and Distributed Visual Representations, [Paper]

• (arXiv 2022.06) GateHUB: Gated History Unit with Background Suppression for Online Action Detection, [Paper]

• (arXiv 2022.06) Anomaly detection in surveillance videos using transformer based attention model, [Paper], [Code]

• (arXiv 2022.06) ContraCLIP: Interpretable GAN generation driven by pairs of contrasting sentences, [Paper], [Code]

• (arXiv 2022.06) EAANet: Efficient Attention Augmented Convolutional Networks, [Paper]

• (arXiv 2022.06) Visual Clues: Bridging Vision and Language Foundations for Image Paragraph Captioning, [Paper]

• (arXiv 2022.06) Recurrent Video Restoration Transformer with Guided Deformable Attention, [Paper], [Code]

• (arXiv 2022.06) Rethinking the Openness of CLIP, [Paper]

• (arXiv 2022.06) OrdinalCLIP: Learning Rank Prompts for Language-Guided Ordinal Regression, [Paper]

• (arXiv 2022.06) Towards Fast Adaptation of Pretrained Contrastive Models for Multi-channel Video-Language Retrieval, [Paper]

• (arXiv 2022.06) CONTRASTIVE GRAPH MULTIMODAL MODEL FOR TEXT CLASSIFICATION IN VIDEOS, [Paper]

• (arXiv 2022.06) Separable Self-attention for Mobile Vision Transformers, [Paper], [Code]

• (arXiv 2022.06) Mask DINO: Towards A Unified Transformer-based Framework for Object Detection and Segmentation, [Paper], [Code]

• (arXiv 2022.06) Multimodal Contrastive Learning with LIMoE: the Language-Image Mixture of Experts, [Paper]

• (arXiv 2022.06) cViL: Cross-Lingual Training of Vision-Language Models using Knowledge Distillation, [Paper]

• (arXiv 2022.06) Masked Unsupervised Self-training for Zero-shot Image Classification, [Paper], [Code]

• (arXiv 2022.06) DETR++: Taming Your Multi-Scale Detection Transformer, [Paper]

• (arXiv 2022.06) Structured Context Transformer for Generic Event Boundary Detection, [Paper]

• (arXiv 2022.06) Revealing Single Frame Bias for Video-and-Language Learning, [Paper], [Code]

• (arXiv 2022.06) Cerberus Transformer: Joint Semantic, Affordance and Attribute Parsing, [Paper], [Code]

• (arXiv 2022.06) Can CNNs Be More Robust Than Transformers? [Paper], [Code]

• (arXiv 2022.06) Detection Hub: Unifying Object Detection Datasets via Query Adaptation on Language Embedding, [Paper]

• (CVPR 2022) Keypoint Transformer: Solving Joint Identification in Challenging Hands and Object Interactions for Accurate 3D Pose Estimation, [Paper]

• (arXiv 2022.06) A-OKVQA: A Benchmark for Visual Question Answering using World Knowledge, [Paper], [Project]

• (arXiv 2022.06) Revisiting the “Video” in Video-Language Understanding, [Paper], [Project]

• (arXiv 2022.06) Efficient Self-supervised Vision Pretraining with Local Masked Reconstruction, [Paper]

• (arXiv 2022.06) Modeling Image Composition for Complex Scene Generation, [Paper], [Code]

• (arXiv 2022.06) Unified Recurrence Modeling for Video Action Anticipation, [Paper]

• (arXiv 2022.06) Prefix Conditioning Unifies Language and Label Supervision, [Paper]

• (arXiv 2022.06) Optimizing Relevance Maps of Vision Transformers Improves Robustness, [Paper], [Code]

• (arXiv 2022.06) VL-BEIT: Generative Vision-Language Pretraining, [Paper], [Code]

• (arXiv 2022.06) EfficientFormer: Vision Transformers at MobileNet Speed, [Paper], [Code]

• (arXiv 2022.06) REVIVE: Regional Visual Representation Matters in Knowledge-Based Visual Question Answering, [Paper]

• (arXiv 2022.06) Siamese Image Modeling for Self-Supervised Vision Representation Learning, [Paper]

• (CVPR 2022) Distillation Using Oracle Queries for Transformer-based Human-Object nteraction Detection, [Paper], [Code]

• (CVPR 2022) Exploring Structure-aware Transformer over Interaction Proposals for Human-Object Interaction Detection, [Paper], [Code]

• (CVPR 2022) Human Trajectory Prediction with Momentary Observation, [Paper]

• (arXiv 2022.06) Where are my Neighbors? Exploiting Patches Relations in Self-Supervised Vision Transformer, [Paper]

• (arXiv 2022.06) Unifying Voxel-based Representation with Transformer for 3D Object Detection, [Paper], [Code]

• (arXiv 2022.06) Extreme Floorplan Reconstruction by Structure-Hallucinating Transformer Cascades, [Paper]

• (arXiv 2022.06) Cross-View Language Modeling: Towards Unified Cross-Lingual Cross-Modal Pre-training, [Paper]

• (arXiv 2022.06) VALHALLA: Visual Hallucination for Machine Translation, [Paper], [Code]

• (arXiv 2022.06) Learning Sequential Contexts using Transformer for 3D Hand Pose Estimation, [Paper]

• (arXiv 2022.06) CLIP4IDC: CLIP for Image Difference Captioning, [Paper], [Code]

• (arXiv 2022.06) Cross-domain Detection Transformer based on Spatial-aware and Semantic-aware Token Alignment, [Paper]

• (arXiv 2022.06) Vision GNN: An Image is Worth Graph of Nodes, [Paper], [Code]

• (arXiv 2022.06) Weakly-supervised Action Transition Learning for Stochastic Human Motion Prediction, [Paper], [Code]

• (arXiv 2022.06) TubeFormer-DeepLab: Video Mask Transformer, [Paper]

• (arXiv 2022.06) Video-based Human-Object Interaction Detection from Tubelet Tokens, [Paper]

2022.05

• (arXiv 2022.05) HeatER: An Efficient and Unified Network for Human Reconstruction via Heatmap-based TransformER, [Paper]

• (arXiv 2022.05) Robotic grasp detection based on Transformer, [Paper]

• (arXiv 2022.05) Multimodal Masked Autoencoders Learn Transferable Representations, [Paper]

• (arXiv 2022.05) Multimodal Fake News Detection via CLIP-Guided Learning, [Paper]

• (arXiv 2022.05) WT-MVSNet: Window-based Transformers for Multi-view Stereo, [Paper]

• (arXiv 2022.05) Object-wise Masked Autoencoders for Fast Pre-training, [Paper]

• (arXiv 2022.05) A Closer Look at Self-supervised Lightweight Vision Transformers, [Paper]

• (arXiv 2022.05) Variational Transformer: A Framework Beyond the Trade-off between Accuracy and Diversity for Image Captioning, [Paper]

• (arXiv 2022.05) CYCLIP: Cyclic Contrastive Language-Image Pretraining, [Paper], [Code]

• (arXiv 2022.05) MDMLP: Image Classification from Scratch on Small Datasets with MLP, [Paper], [Code]

• (arXiv 2022.05) SupMAE: Supervised Masked Autoencoders Are Efficient Vision Learners, [Paper], [Code]

• (arXiv 2022.05) 3D-C2FT: Coarse-to-fine Transformer for Multi-view 3D Reconstruction, [Paper]

• (arXiv 2022.05) Prompt-aligned Gradient for Prompt Tuning, [Paper], [Code]

• (arXiv 2022.05) Illumination Adaptive Transformer, [Paper], [Code]

• (arXiv 2022.05) HiViT: Hierarchical Vision Transformer Meets Masked Image Modeling, [Paper]

• (arXiv 2022.05) GMML is All you Need, [Paper], [Code]

• (arXiv 2022.05) COMPLETEDT: POINT CLOUD COMPLETION WITH DENSE AUGMENT INFERENCE TRANSFORMERS, [Paper]

• (arXiv 2022.05) Self-Supervised Pre-training of Vision Transformers for Dense Prediction Tasks, [Paper]

• (arXiv 2022.05) VLUE: A Multi-Task Benchmark for Evaluating Vision-Language Models, [Paper], [Benchmark], [Code]

• (arXiv 2022.05) Architecture-Agnostic Masked Image Modeling – From ViT back to CNN, [Paper]

• (arXiv 2022.05) Contrastive Learning Rivals Masked Image Modeling in Fine-tuning via Feature Distillation, [Paper], [Code]

• (arXiv 2022.05) GIT: A Generative Image-to-text Transformer for Vision and Language, [Paper]

• (arXiv 2022.05) 3DILG: Irregular Latent Grids for 3D Generative Modeling, [Paper]

• (arXiv 2022.05) Simple Unsupervised Object-Centric Learning for Complex and Naturalistic Videos, [Paper], [Code]

• (arXiv 2022.05) Future Transformer for Long-term Action Anticipation, [Paper], [Project]

• (arXiv 2022.05) X-ViT: High Performance Linear Vision Transformer without Softmax, [Paper]

• (arXiv 2022.05) Knowledge Distillation via the Target-aware Transformer, [Paper]

• (arXiv 2022.05) Dynamic Query Selection for Fast Visual Perceiver, [Paper]

• (arXiv 2022.05) MonoFormer: Towards Generalization of self-supervised monocular depth estimation with Transformers, [Paper]

• (arXiv 2022.05) PEVL: Position-enhanced Pre-training and Prompt Tuning for Vision-language Models, [Paper], [Code]

• (arXiv 2022.05) Supporting Vision-Language Model Inference with Causality-pruning Knowledge Prompt, [Paper]

• (arXiv 2022.05) Super Vision Transformer, [Paper], [Code]

• (arXiv 2022.05) mPLUG: Effective and Efficient Vision-Language Learning by Cross-modal Skip-connections, [Paper]

• (arXiv 2022.05) VQA-GNN: Reasoning with Multimodal Semantic Graph for Visual Question Answering, [Paper]

• (arXiv 2022.05) UMSNet: An Universal Multi-sensor Network for Human Activity Recognition, [Paper]

• (arXiv 2022.05) Privacy-Preserving Image Classification Using Vision Transformer, [Paper]

• (arXiv 2022.05) HiVLP: Hierarchical Vision-Language Pre-Training for Fast Image-Text Retrieval, [Paper]

• (arXiv 2022.05) ASSET: Autoregressive Semantic Scene Editing with Transformers at High Resolutions, [Paper], [Code]

• (arXiv 2022.05) HDGT: Heterogeneous Driving Graph Transformer for Multi-Agent Trajectory Prediction via Scene Encoding, [Paper]

• (arXiv 2022.05) Mask-guided Vision Transformer (MG-ViT) for Few-Shot Learning, [Paper]

• (arXiv 2022.05) Degradation-Aware Unfolding Half-Shuffle Transformer for Spectral Compressive Imaging, [Paper]

• (arXiv 2022.05) Uniform Masking: Enabling MAE Pre-training for Pyramid-based Vision Transformers with Locality, [Paper], [Code]

• (arXiv 2022.05) Visual Concepts Tokenization, [Paper]

• (arXiv 2022.05) MSTRIQ: No Reference Image Quality Assessment Based on Swin Transformer with Multi-Stage Fusion, [Paper]

• (arXiv 2022.05) CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers., [Paper], [Code]

• (arXiv 2022.05) Evidence for Hypodescent in Visual Semantic AI, [Paper]

• (arXiv 2022.05) Boosting Camouflaged Object Detection with Dual-Task Interactive Transformer, [Paper], [Code]

• (arXiv 2022.05) muNet: Evolving Pretrained Deep Neural Networks into Scalable Auto-tuning Multitask Systems, [Paper]

• (arXiv 2022.05) Large Language Models are Zero-Shot Reasoners, [Paper]

• (arXiv 2022.05) AdaptFormer: Adapting Vision Transformers for Scalable Visual Recognition, [Paper], [Code]

• (arXiv 2022.05) Green Hierarchical Vision Transformer for Masked Image Modeling, [Paper], [Code]

• (arXiv 2022.05) Efficient U-Transformer with Boundary-Aware Loss for Action Segmentation, [Paper]

• (arXiv 2022.05) Cross-Architecture Self-supervised Video Representation Learning, [Paper], [Code]

• (arXiv 2022.05) Prompt-based Learning for Unpaired Image Captioning, [Paper]

• (arXiv 2022.05) MixMIM: Mixed and Masked Image Modeling for Efficient Visual Representation Learning, [Paper], [Code]

• (arXiv 2022.05) Fast Vision Transformers with HiLo Attention, [Paper], [Code]

• (arXiv 2022.05) Fine-grained Image Captioning with CLIP Reward, [Paper], [Code]

• (arXiv 2022.05) Mutual Information Divergence: A Unified Metric for Multimodal Generative Models, [Paper]

• (arXiv 2022.05) MoCoViT: Mobile Convolutional Vision Transformer, [Paper]

• (arXiv 2022.05) AO2-DETR: Arbitrary-Oriented Object Detection Transformer, [Paper]

• (arXiv 2022.05) Inception Transformer, [Paper], [Code]

• (arXiv 2022.05) VTP: Volumetric Transformer for Multi-view Multi-person 3D Pose Estimation, [Paper]

• (arXiv 2022.05) UViM: A Unified Modeling Approach for Vision with Learned Guiding Codes, [Paper]

• (arXiv 2022.05) Language Models with Image Descriptors are Strong Few-Shot Video-Language Learners, [Paper], [Code]

• (arXiv 2022.05) Training Vision-Language Transformers from Captions Alone, [Paper], [Code]

• (arXiv 2022.05) Voxel-informed Language Grounding, [Paper], [Code]

• (arXiv 2022.05) Cross-Enhancement Transformer for Action Segmentation, [Paper]

• (arXiv 2022.05) TRT-ViT: TensorRT-oriented Vision Transformer, [Paper]

• (arXiv 2022.05) Integral Migrating Pre-trained Transformer Encoder-decoders for Visual Object Detection, [Paper]

• (arXiv 2022.05) A graph-transformer for whole slide image classification, [Paper]

• (arXiv 2022.05) VNT-Net: Rotational Invariant Vector Neuron Transformers, [Paper]

• (arXiv 2022.05) Masked Image Modeling with Denoising Contrast, [Paper]

• (arXiv 2022.05) Cross-subject Action Unit Detection with Meta Learning and Transformer-based Relation Modeling, [Paper]

• (arXiv 2022.05) Masked Autoencoders As Spatiotemporal Learners, [Paper]

• (arXiv 2022.05) BodyMap: Learning Full-Body Dense Correspondence Map, [Paper], [Code]

• (arXiv 2022.05) Unraveling Attention via Convex Duality: Analysis and Interpretations of Vision Transformers, [Paper]

• (arXiv 2022.05) AvatarCLIP: Zero-Shot Text-Driven Generation and Animation of 3D Avatars, [Paper]

• (arXiv 2022.05) Vision Transformer Adapter for Dense Predictions, [Paper], [Code]

• (arXiv 2022.05) Demo: Real-Time Semantic Communications with a Vision Transformer, [Paper]

• (arXiv 2022.05) MulT: An End-to-End Multitask Learning Transformer, [Paper], [Code]

• (arXiv 2022.05) A CLIP-Hitchhiker’s Guide to Long Video Retrieval, [Paper]

• (arXiv 2022.05) Video Frame Interpolation with Transformer, [Paper], [Code]

• (arXiv 2022.05) Dense residual Transformer for Image Denoising, [Paper]

• (arXiv 2022.05) Learning Lip-Based Audio-Visual Speaker Embeddings with AV-HuBERT, [Paper]

• (arXiv 2022.05) Robot Cooking with Stir-fry: Bimanual Non-prehensile Manipulation of Semi-fluid Objects, [Paper]

• (arXiv 2022.05) Entity-aware and Motion-aware Transformers for Language-driven Action Localization in Videos, [Paper], [Code]

• (arXiv 2022.05) Learning to Retrieve Videos by Asking Questions, [Paper]

• (arXiv 2022.05) One Model, Multiple Modalities: A Sparsely Activated Approach for Text, Sound, Image, Video and Code, [Paper]

• (arXiv 2022.05) Simple Open-Vocabulary Object Detection with Vision Transformers, [Paper], [Code]

• (arXiv 2022.05) AggPose: Deep Aggregation Vision Transformer for Infant Pose Estimation, [Paper], [Code]

• (arXiv 2022.05) An Empirical Study of Self-supervised Learning Approaches for Object Detection with Transformers, [Paper], [Code-DETR], [Code-Deform-DETR]

• (arXiv 2022.05) Reduce Information Loss in Transformers for Pluralistic Image Inpainting, [Paper], [Code]

• (arXiv 2022.05) Transformer-based Cross-Modal Recipe Embeddings with Large Batch Training, [Paper]

• (arXiv 2022.05) Spatio-Temporal Transformer for Dynamic Facial Expression Recognition in the Wild, [Paper]

• (arXiv 2022.05) Generalizable Task Planning through Representation Pretraining, [Paper], [Project]

• (arXiv 2022.05) EdgeViTs: Competing Light-weight CNNs on Mobile Devices with Vision Transformers, [Paper]

• (arXiv 2022.05) Activating More Pixels in Image Super-Resolution Transformer, [Paper], [Code]

• (arXiv 2022.05) Row-wise Accelerator for Vision Transformer, [Paper]

• (arXiv 2022.05) SparseTT: Visual Tracking with Sparse Transformers, [Paper], [Code]

• (arXiv 2022.05) RoViST: Learning Robust Metrics for Visual Storytelling, [Paper], [Code]

• (arXiv 2022.05) Beyond Bounding Box: Multimodal Knowledge Learning for Object Detection, [Paper]

• (arXiv 2022.05) Multilevel Hierarchical Network with Multiscale Sampling for Video Question Answering, [Paper]

• (arXiv 2022.05) Incremental-DETR: Incremental Few-Shot Object Detection via Self-Supervised Learning, [Paper]

• (arXiv 2022.05) ConvMAE: Masked Convolution Meets Masked Autoencoders, [Paper], [Code]

• (arXiv 2022.05) Cross-lingual Adaptation for Recipe Retrieval with Mixup, [Paper]

• (arXiv 2022.05) Zero and R2D2: A Large-scale Chinese Cross-modal Benchmark and A Vision-Language Framework, [Paper]

• (arXiv 2022.05) Transformer Tracking with Cyclic Shifting Window Attention, [Paper], [Code]

• (arXiv 2022.05) Beyond a Pre-Trained Object Detector: Cross-Modal Textual and Visual Context for Image Captioning, [Paper]

• (arXiv 2022.05) Prompt Distribution Learning, [Paper]

• (arXiv 2022.05) CLIP-CLOP: CLIP-Guided Collage and Photomontage, [Paper]

• (arXiv 2022.05) Dual-Level Decoupled Transformer for Video Captioning, [Paper]

• (arXiv 2022.05) Declaration-based Prompt Tuning for Visual Question Answering, [Paper], [Code]

• (arXiv 2022.05) P^3IV: Probabilistic Procedure Planning from Instructional Videos with Weak Supervision, [Paper]

• (arXiv 2022.05) Language Models Can See: Plugging Visual Controls in Text Generation, [Paper], [Code]

• (arXiv 2022.05) YOLOPose: Transformer-based Multi-Object 6D Pose Estimation using Keypoint Regression, [Paper]

• (arXiv 2022.05) Cross-view Transformers for real-time Map-view Semantic Segmentation, [Paper], [Code]

• (arXiv 2022.05) i-Code: An Integrative and Composable Multimodal Learning Framework, [Paper]

• (arXiv 2022.05) Visual Commonsense in Pretrained Unimodal and Multimodal Models, [Paper], [Project]

• (arXiv 2022.05) Dual Cross-Attention Learning for Fine-Grained Visual Categorization and Object Re-Identification, [Paper]

• (arXiv 2022.05) RecipeSnap - a lightweight image to recipe model, [Paper], [Code]

• (arXiv 2022.05) CoCa: Contrastive Captioners are Image-Text Foundation Models, [Paper]

• (arXiv 2022.05) Data Determines Distributional Robustness in Contrastive Language Image Pre-training (CLIP), [Paper]

• (arXiv 2022.05) Cross-modal Representation Learning for Zero-shot Action Recognition, [Paper], [Code]

• (arXiv 2022.05) Cross-Domain Object Detection with Mean-Teacher Transformer, [Paper]

• (arXiv 2022.05) Better plain ViT baselines for ImageNet-1k, [Paper], [Code]

• (arXiv 2022.05) Reinforced Swin-Convs Transformer for Underwater Image Enhancement, [Paper]

• (arXiv 2022.05) UTC: A Unified Transformer with Inter-Task Contrastive Learning for Visual Dialog, [Paper]

• (arXiv 2022.05) Answer-Me: Multi-Task Open-Vocabulary Visual Question Answering, [Paper]

• (arXiv 2022.05) CenterCLIP: Token Clustering for Efficient Text-Video Retrieval, [Paper], [Code]

• (arXiv 2022.05) Arbitrary Shape Text Detection via Boundary Transformer, [Paper], [Code]

• (arXiv 2022.05) HULC: 3D Human Motion Capture with Pose Manifold Sampling and Dense Contact Guidance, [Paper], [Project]