Routing Evidence for Unseen Actions in Video Moment Retrieval-Reference-Cited by-同舟云学术

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Routing Evidence for Unseen Actions in Video Moment Retrieval

Published:2024-08-24 Issue: Volume:33 Page:3024-3035
ISSN:
Container-title:Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Wang Guolong¹^ORCID,Wu Xun²^ORCID,Qin Zheng²^ORCID,Shi Liangliang³^ORCID

Affiliation:

1. School of Information Technology & Management, University of International Business and Economics, Beijing, China

2. Tsinghua University, Beijing, China

3. School of Artificial Intelligence & Department of Computer Science and Engineering & MoE Lab of AI, Shanghai Jiao Tong University, Shanghai, China

Funder

Scientific Research Laboratory of AI Technology and Applications, University of International Business and Economics

the Fundamental Research Funds for the Central Universities in UIBE

the Open Projects Program of State Key Laboratory of Multimodal Artificial Intelligence Systems

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3637528.3671693

Reference62 articles.

1. Deep evidential regression;Amini Alexander;Advances in Neural Information Processing Systems,2020

2. Localizing Moments in Video with Natural Language

3. Evidential Deep Learning for Open Set Action Recognition

4. OpenTAL: Towards Open Set Temporal Action Localization

5. Joao Carreira and Andrew Zisserman. 2018. Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset. arXiv preprint arXiv:1705.07750 (2018).

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