Unsupervised Action Recognition
Unsupervised Action Recognition is a subfield of action recognition in computer vision that identifies human actions in video sequences without relying on labeled training data, distinguishing itself by leveraging unsupervised learning techniques to discover and categorize action patterns directly from raw or unannotated video inputs.
138
Publications
7.9K
Citations
474
Authors
186
Institutions
Publications per year
2017–2026
76
Parents
138
3D Human Action Representation Learning via Cross-View Consistency Pursuit
Linguo Li, Minsi Wang, Bingbing Ni et al. · 2021 · 216 citations
PREDICT & CLUSTER: Unsupervised Skeleton Based Action Recognition
Kun Su, Xiulong Liu, Eli Shlizerman · 2020 · 211 citations
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186
Stanford University
Stanford, United States
6 h-index
23 publications
4.8K citations
Carnegie Mellon University
Pittsburgh, United States
5 h-index
13 publications
412 citations

Chinese Academy of Sciences
Beijing, China
5 h-index
14 publications
1.3K citations
Institut national de recherche en sciences et technologies du numérique
Le Chesnay-Rocquencourt, France
4 h-index
14 publications
596 citations
Nanyang Technological University
Singapore, Singapore
4 h-index
9 publications
592 citations
Tsinghua University
Beijing, China
4 h-index
14 publications
663 citations
The University of Tokyo
Tokyo, Japan
4 h-index
11 publications
339 citations

Shanghai Jiao Tong University
Shanghai, China
4 h-index
17 publications
1.7K citations
1–8 of 186
Repository · 16 publications · 441 citations
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Conference · 5 publications · 406 citations
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4 publications · 178 citations
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2 publications · 111 citations
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Conference · 2 publications · 73 citations
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