Weakly Supervised Action Recognition
Weakly Supervised Action Recognition is a subfield of video action recognition that leverages incomplete, imprecise, or noisy supervision—such as video-level labels without precise temporal boundaries—during model training, distinguishing it from fully supervised approaches that require frame-level annotations.
221
Publications
13.3K
Citations
680
Authors
271
Institutions
Publications per year
2017–2026
180
Parents
221
The THUMOS challenge on action recognition for videos “in the wild”
Haroon Idrees, Amir Zamir, Yu–Gang Jiang et al. · Computer Vision and Image Understanding · 2016 · 589 citations · Full text
UntrimmedNets for Weakly Supervised Action Recognition and Detection
Limin Wang, Yuanjun Xiong, Dahua Lin et al. · 2017 · 571 citations
Weakly Supervised Action Localization by Sparse Temporal Pooling Network
Phuc Nguyen, Bohyung Han, Ting Liu et al. · 2018 · 423 citations
1–5 of 221
680
Institut national de recherche en sciences et technologies du numérique, France
7 publications · 1K citations
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7
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7
h-index
6
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6
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1–5 of 680
271

Chinese Academy of Sciences
Beijing, China
20 h-index
63 publications
2.2K citations
Institute of Automation
Beijing, China
13 h-index
38 publications
1.3K citations
University of Chinese Academy of Sciences
Beijing, China
13 h-index
24 publications
1K citations
Peng Cheng Laboratory
Shenzhen, China
9 h-index
11 publications
872 citations

Xi'an Jiaotong University
Xi'an, China
8 h-index
23 publications
1.1K citations

Beijing Institute of Technology
Beijing, China
8 h-index
11 publications
317 citations

Peking University
Beijing, China
8 h-index
22 publications
2.3K citations
Beijing Academy of Artificial Intelligence
Beijing, China
7 h-index
11 publications
434 citations
1–8 of 271
Repository · 19 publications · 579 citations
14
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13 publications · 378 citations
13
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11 publications · 407 citations
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TPAMI · 10 publications · 692 citations
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Conference · 9 publications · 477 citations
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1–5