Progressive Instance-Aware Feature Learning for Compositional Action Recognition

Author:

Yan Rui1ORCID,Xie Lingxi2ORCID,Shu Xiangbo1ORCID,Zhang Liyan3ORCID,Tang Jinhui1ORCID

Affiliation:

1. School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu, China

2. Huawei Inc., Shenzhen, Guangdong, China

3. College of Computer Science and Technology, MIIT Key Laboratory of Pattern Analysis and Machine Intelligence, Collaborative Innovation Center of Novel Software Technology and Industrialization, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Computer Vision and Pattern Recognition,Software

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3. Discriminative Action Snippet Propagation Network for Weakly Supervised Temporal Action Localization;ACM Transactions on Multimedia Computing, Communications, and Applications;2024-03-08

4. DMMG: Dual Min-Max Games for Self-Supervised Skeleton-Based Action Recognition;IEEE Transactions on Image Processing;2024

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