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SVMFN-FSAR:Semantic-Guided Video Multimodal Fusion Network for Few-Shot Action Recognition

Ran Wei Rui Yan Hongyu Qu Xing Li Qiaolin Ye Liyong Fu

大数据挖掘与分析（英文版）2025，Vol.8Issue(3)：534-550,17.

大数据挖掘与分析（英文版）2025，Vol.8Issue(3)：534-550,17.DOI:10.26599/BDMA.2024.9020076

SVMFN-FSAR:Semantic-Guided Video Multimodal Fusion Network for Few-Shot Action Recognition

Ran Wei ¹Rui Yan ²Hongyu Qu ³Xing Li ¹Qiaolin Ye ¹Liyong Fu⁴

作者信息

1. College of Information Science and Technology & Artificial Intelligence,with State Key Laboratory of Tree Genetics and Breeding||Co-Innovation Center for Sustainable Forestry in Southern China,Nanjing Forestry University,Nanjing 210037,China
2. Department of Computer Science and Technology,Nanjing University,Nanjing 210023,China
3. School of Computer Science and Engineering,Nanjing University of Science and Technology,Nanjing 210094,China
4. College of Forestry,Hebei Agricultural University,Baoding 071000,China||Institute of Forest Resource Information Techniques,Chinese Academy of Forestry,Beijing 100091,China
折叠

摘要

关键词

few-shot learning/action recognition/Large Language Model(LLM)/Transformer/video understanding

Key words

few-shot learning/action recognition/Large Language Model(LLM)/Transformer/video understanding

引用本文复制引用

Ran Wei,Rui Yan,Hongyu Qu,Xing Li,Qiaolin Ye,Liyong Fu..SVMFN-FSAR:Semantic-Guided Video Multimodal Fusion Network for Few-Shot Action Recognition[J].大数据挖掘与分析（英文版）,2025,8(3):534-550,17.

基金项目

This work was supported by the National Key Research and Development Program(No.2022YFD2201005),the National Natural Science Foundation of China(Nos.62072246 and 32371877),the Postdoctoral Fellowship Program of CPSF(No.GZB20230302),and the Construction of Forest Fire Prevention Comprehensive System in Chongli District,Jiakou City(Unmanned Aerial Vehicle Patrol Monitoring System)(No.DA2020001). （No.2022YFD2201005）

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