燕山大学学报2026，Vol.50Issue(4)：338-347,359,11.DOI:10.3969/j.issn.1007-791X.2026.04.007
基于通道自注意和时空并行感知的体育动作质量评估网络
Sports action quality assessment network based on tube self-attention and spatiotemporal parallel perception
摘要
Abstract
The quality assessment of sports actions requires providing quality ratings for the completeness,fluency,and difficulty of actions based on the recognition of action types,which is extremely challenging.A network structure based on tube self-attention and spatiotemporal parallel perception was designed to accurately extract key information from action sequences and efficiently assess action quality.Firstly,action information was extracted and background interference was eliminated using a single target tracking and tube self-attention module.Secondly,based on the Uniformer model,a spatial multi-head self-attention mechanism was introduced in the local feature extraction module,and the local and global attention spatiotemporal serial perception network was changed to a spatiotemporal parallel perception network to improve computational efficiency.Finally,the local and global features were fused through a multi-stage fusion module to enhance action representation,and the multi-layer perceptron module was extended to output action recognition and action quality assessment results.Action recognition experiments were conducted on the UCF101 and HMDB51 dataset,respectively.The action recognition Top-l and Top-5 accuracy of the UCF101 dataset reached 85.2％and 96.7％,respectively,and the computational cost of FLOPs significantly decreased,the action recognition accuracy Top-1 of the HMDB51 dataset reached 77.8％.Action quality assessment experiments were conducted on the AQA-7 and MTL-AQA dataset,respectively,the average Spearman's rank correlation coefficient for the assessment of the AQA-7 dataset reached 0.808 7,the Spearman's rank correlation coefficient for the assessment of the MTL-AQA dataset reached 0.948 1.The experimental results show that the model not only has a high action recognition rate,but also can accurately and efficiently complete the task of action quality assessment.关键词
动作质量评估/视频动作识别/Uniformer/通道自注意力/时空并行感知Key words
action quality assessment/video action recognition/Uniformer/tube self-attention/spatiotemporal parallel perception分类
信息技术与安全科学引用本文复制引用
邢素霞,郭正,方俊泽,于重重,范福强..基于通道自注意和时空并行感知的体育动作质量评估网络[J].燕山大学学报,2026,50(4):338-347,359,11.基金项目
北京市自然科学基金资助项目(4174086) （4174086）
辽宁省自然科学基金资助项目(2020-KF-23-06) （2020-KF-23-06）
