Fitness-AQA
Fitness-AQA is an AI-based system for assessing workout form and detecting posture errors during exercise, introduced at ECCV 2022. Designed for real-world gym scenarios, it analyzes video to evaluate exercise quality even under challenging conditions such as difficult camera angles, varied clothing, occlusion from gym equipment, and other factors that typically cause standard pose estimators to fail. The system currently targets three exercises: BackSquat, OverheadPress, and BarbellRow. It employs multiple self-supervised representation learning methods, including a pose contrastive learning framework, a motion disentangling approach, and a pose and appearance disentangling technique, as well as a quasi-synchronization method for handling in-the-wild video footage. The project also introduces the Fitness-AQA dataset, the largest fine-grained exercise action quality assessment dataset, available for non-commercial research upon request. Use cases include AI fitness coaching, injury prevention through form cor