A Decade of Action Quality Assessment: Largest Systematic Survey of Trends, Challenges, and Future Directions

2025-02-05

AI Summary

Action Quality Assessment (AQA) has advanced rapidly, yet lacks a systematic, evidence-based survey. To address this gap, we conduct the first large-scale, structured review of over 200 papers published in the past decade, following the PRISMA evidence synthesis framework. Our analysis unifies definitions, methodologies, benchmark datasets, and evaluation metrics across computer vision, video understanding, biomechanical motion analysis, and domain-specific applications in education and healthcare. We identify key research trends, persistent challenges—including data bias, poor generalizability, and limited interpretability of feedback—and cross-scenario technical bottlenecks. Based on this analysis, we propose a structured roadmap for algorithmic optimization and system-level design, delineate performance boundaries of mainstream approaches, and release an open-source review platform. This work establishes an authoritative benchmark and practical guideline for the AQA research community.

Technology Category

• Computer Vision: Video Understanding & Activity Analysis
• Humans and AI: Human-Aware Planning and Behavior Prediction
• Knowledge Representation and Reasoning: Qualitative Reasoning

Application Category

• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets

Abstract

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/

Problem

• Comprehensive synthesis of AQA methodologies
• Systematic review of 200+ AQA research papers
• Analysis of trends, challenges, and future directions

Innovation

• Systematic survey using PRISMA framework
• Review of over 200 AQA research papers
• Detailed analysis of trends and challenges