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21 July 2023 A novel blind action quality assessment based on multi-headed GRU network and attention mechanism
WenHao Sun, YanXiang Hu, Bo Zhang, XinRan Chen, CaiXia Hao, YaRu Gao
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Proceedings Volume 12717, 3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2023); 1271737 (2023) https://doi.org/10.1117/12.2685368
Event: 3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2023), 2023, Wuhan, China
Abstract
Objective action quality assessment (AQA) is a complex machine vision task because existing AQA assessment models can’t effectively fit the subjective assessment. To address this issue, we propose a novel blind action quality assessment method. By processing the video data with spatial and temporal features, the performance of the model is effectively improved. In addition, we also proposed a new loss function to better train the model, which combines the information entropy of the data. Finally, the experimental results show that on the existing datasets AQA-7 and JIGSAWS are significantly improved, reaching 0.63 and 0.57, respectively.
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WenHao Sun, YanXiang Hu, Bo Zhang, XinRan Chen, CaiXia Hao, and YaRu Gao "A novel blind action quality assessment based on multi-headed GRU network and attention mechanism", Proc. SPIE 12717, 3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing (AIAHPC 2023), 1271737 (21 July 2023); https://doi.org/10.1117/12.2685368
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KEYWORDS
Video
Feature extraction
Deep learning
Video processing
Design and modelling
Neural networks
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