系统梳理十年动作质量评估研究，揭示趋势与挑战
A Decade of Action Quality Assessment: Largest Systematic Survey of Trends, Challenges, and Future Directions
- 基于PRISMA框架调研200+论文，构建系统性分析框架
- 对比多种方法在常见数据集上的表现，识别性能瓶颈
- 适合初学者入门及资深研究者把握未来方向
动作质量评估（AQA）——量化人类运动、动作或技能水平并提供反馈的能力——在低成本理疗、体育训练和职业发展等领域具有深远意义。过去十年间，该领域已成为计算机视觉与视频理解的重要方向。尽管方法、数据集和应用方面已取得显著进展，但对这一快速发展的领域的全面整合仍显不足。本文基于系统综述与元分析的首选报告条目（PRISMA）框架，系统回顾了超过200篇相关研究。从基础概念与定义出发，涵盖通用框架与评估指标，深入探讨最新方法与数据集进展。本综述对研究趋势、性能比较、现存挑战及未来方向进行了详细分析，旨在为初学者与资深研究人员提供宝贵参考资源，推动AQA领域持续发展。数据可在 https://haoyin116.github.io/Survey_of_AQA/ 获取。
原文摘要 · Abstract (English)
Action Quality Assessment (AQA) -- the ability to quantify the quality of human motion, actions, or skill levels and provide feedback -- has far-reaching implications in areas such as low-cost physiotherapy, sports training, and workforce development. As such, it has become a critical field in computer vision & video understanding over the past decade. Significant progress has been made in AQA methodologies, datasets, & applications, yet a pressing need remains for a comprehensive synthesis of this rapidly evolving field. In this paper, we present a thorough survey of the AQA landscape, systematically reviewing over 200 research papers using the preferred reporting items for systematic reviews & meta-analyses (PRISMA) framework. We begin by covering foundational concepts & definitions, then move to general frameworks & performance metrics, & finally discuss the latest advances in methodologies & datasets. This survey provides a detailed analysis of research trends, performance comparisons, challenges, & future directions. Through this work, we aim to offer a valuable resource for both newcomers & experienced researchers, promoting further exploration & progress in AQA. Data are available at https://haoyin116.github.io/Survey_of_AQA/
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