Skeleton-Based Action Recognition is a method within the field of action recognition that utilizes skeletal joint data to represent and analyze human motion, distinguishing itself by focusing on the geometric configuration and dynamics of body keypoints rather than raw visual input.
846
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76.3K
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2.3K
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705
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Publications per year
2017–2026
706
Variants
Skeleton-based Human Action Recognition
Parents
Publications
846
Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition
Lei Shi, Yifan Zhang, Jian Cheng et al. · 2019 · 2K citations
View invariant human action recognition using histograms of 3D joints
Lu Xia, Chia-Chih Chen, J.K. Aggarwal · 2012 · 1.5K citations
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Institutions
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Chinese Academy of Sciences
Beijing, China
41 h-index
164 publications
45.9K citations
University of Chinese Academy of Sciences
Beijing, China
31 h-index
114 publications
35.4K citations
Peking University
Beijing, China
29 h-index
82 publications
13.4K citations
Institute of Automation
Beijing, China
22 h-index
65 publications
11.7K citations
Xi'an Jiaotong University
Xi'an, China
21 h-index
52 publications
7.5K citations
Shanghai Jiao Tong University
Shanghai, China
18 h-index
79 publications
9.6K citations
Nanyang Technological University
Singapore, Singapore
18 h-index
40 publications
9.9K citations
Xidian University
Xi'an, China
18 h-index
82 publications
3.8K citations
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- arXiv (Cornell University)
Repository · 72 publications · 3.5K citations
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- IEEE Transactions on Multimedia
25 publications · 1.6K citations
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- IEEE Access
41 publications · 1.2K citations
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- IEEE Transactions on Circuits and Systems for Video Technology
26 publications · 2K citations
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- IEEE Transactions on Image Processing
22 publications · 3K citations
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