SEINE

SEINE is a short-to-long video diffusion model presented at ICLR 2024 designed for high-quality generative video tasks. It addresses the challenge of extending brief input clips into coherent, temporally consistent longer videos while maintaining visual fidelity. The model excels at two primary functions: generative transition, which seamlessly interpolates between two provided video frames or short clips, and long-term prediction, which extrapolates future frames from a short input sequence. SEINE leverages a diffusion-based architecture to synthesize realistic dynamics and textures over extended durations, overcoming common issues like motion blur and conceptual drift often found in longer video synthesis. By focusing on the transition from short observations to long-range predictions, SEINE enables applications in video editing, content creation, and simulation where predicting future events or bridging temporal gaps with plausible media is required. Its approach ensures that the generated content remains