Multimodal Global Relation Knowledge Distillation for Egocentric Action Anticipation

Author:

Huang Yi1,Yang Xiaoshan2,Xu Changsheng3

Affiliation:

1. Institute of Automation, Chinese Academy of Sciences & University of Chinese Academy of Sciences, Beijing, China

2. Institute of Automation, Chinese Academy of Sciences; University of Chinese Academy of Sciences; & Peng Cheng Lab, Beijing, China

3. Institute of Automation, Chinese Academy of Sciences; University of Chinese Academy of Sciences; Peng Cheng Lab; & CASIA-LLVision Joint Lab, Beijing, China

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Publisher

ACM

Reference54 articles.

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Deep contrastive representation learning for multi-modal clustering;Neurocomputing;2024-05

2. A multivariate Markov chain model for interpretable dense action anticipation;Neurocomputing;2024-03

3. Toward Egocentric Compositional Action Anticipation with Adaptive Semantic Debiasing;ACM Transactions on Multimedia Computing, Communications, and Applications;2024-01-11

4. Egocentric Action Prediction via Knowledge Distillation and Subject-Action Relevance;Communications in Computer and Information Science;2024

5. Slowfast Diversity-aware Prototype Learning for Egocentric Action Recognition;Proceedings of the 31st ACM International Conference on Multimedia;2023-10-26

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