Boosting Few-shot Action Recognition with Graph-guided Hybrid Matching

Author:

Xing Jiazheng1,Wang Mengmeng1,Ruan Yudi1,Chen Bofan1,Guo Yaowei1,Mu Boyu1,Dai Guang2,Wang Jingdong3,Liu Yong1

Affiliation:

1. Zhejiang University

2. SGIT AI Lab

3. Baidu Inc.

Publisher

IEEE

Reference47 articles.

1. ViViT: A Video Vision Transformer

2. Is space-time attention all you need for video understanding?;Bertasius

3. Tarn: Temporal attentive relation network for few-shot and zero-shot action recognition;Bishay,2019

4. Few-Shot Video Classification via Temporal Alignment

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

Cited by 5 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. Text-guided Graph Temporal Modeling for few-shot video classification;Engineering Applications of Artificial Intelligence;2024-11

2. Cross-modal guides spatio-temporal enrichment network for few-shot action recognition;Applied Intelligence;2024-08-13

3. Multimodal Prototype-Enhanced Network for Few-Shot Action Recognition;Proceedings of the 2024 International Conference on Multimedia Retrieval;2024-05-30

4. Mask guided two-stream network for end-to-end few-shot action recognition;Neurocomputing;2024-05

5. Matching Compound Prototypes for Few-Shot Action Recognition;International Journal of Computer Vision;2024-04-29

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