Directly Locating Actions in Video with Single Frame Annotation

Author:

Tong Haoran1ORCID,Liu Xinyan1ORCID,Li Guorong2ORCID,Qing Laiyun1ORCID

Affiliation:

1. University of Chinese Academy of Sciences, Beijing, China

2. University of Chinese Academy of Sciences, Bejing, China

Funder

Supported by the Fundamental Research Funds for the Central Universities

Publisher

ACM

Reference29 articles.

1. Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset

2. Yu-Wei Chao, Sudheendra Vijayanarasimhan, Bryan Seybold, David A. Ross, Jia Deng, and Rahul Sukthankar. 2018. Rethinking the Faster R-CNN Architecture for Temporal Action Localization. In CVPR. Computer Vision Foundation / IEEE Computer Society, 1130--1139.

3. Mengyuan Chen, Junyu Gao, Shicai Yang, and Changsheng Xu. 2022. Dual-Evidential Learning for Weakly-supervised Temporal Action Localization. In ECCV (4) (Lecture Notes in Computer Science, Vol. 13664). Springer, 192--208.

4. Feng Cheng and Gedas Bertasius. 2022. TallFormer: Temporal Action Localization with a Long-Memory Transformer. In ECCV (34) (Lecture Notes in Computer Science, Vol. 13694). Springer, 503--521.

5. Dima Damen, Teesid Leelasawassuk, Osian Haines, Andrew Calway, and Walterio W. Mayol-Cuevas. 2014. You-Do, I-Learn: Discovering Task Relevant Objects and their Modes of Interaction from Multi-User Egocentric Video. In BMVC. BMVA Press.

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