Action Quality Assessment
21 papers with code • 6 benchmarks • 7 datasets
Assessing/analyzing/quantifying how well an action was performed.
Can performance on the task of action quality assessment (AQA) be improved by exploiting a description of the action and its quality?
The hallucination task is treated as an auxiliary task, which can be used with any other action related task in a multitask learning setting.
However, most existing works focus only on video dynamic information (i. e., motion information) but ignore the specific postures that an athlete is performing in a video, which is important for action assessment in long videos.
Traditionally, AQA is treated as a regression problem to learn the underlying mappings between videos and action scores.
Action quality assessment (AQA) has become an emerging topic since it can be extensively applied in numerous scenarios.
In this paper, we propose a deep learning-based framework for automated assessment of the quality of physical rehabilitation exercises.