Action Quality Assessment
Overview
Action quality assessment studies how to judge the correctness, proficiency, or value of human actions, from rehabilitation exercises and sports techniques to tactical decisions in team games. Methods use video and pose sequences, temporal and phase-based modeling, self-supervised representations, multimodal fusion, and sometimes wearable sensors to predict scores, rank performers, or locate errors. Recent work also explores vision-language models and language-based feedback, but fine-grained judgments remain difficult for these models, and explanations need to be grounded in reliable visual or sensor evidence. A central challenge is making assessments robust to camera views, missing or noisy modalities, and differences between action types while keeping feedback interpretable and useful to human reviewers.
Latest papers
23 papers2 papers in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.