A Progressive Difference Method for Capturing Visual Tempos on Action Recognition-Reference-Cited by-同舟云学术

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A Progressive Difference Method for Capturing Visual Tempos on Action Recognition

Published:2023-03 Issue:3 Volume:33 Page:977-987
ISSN:1051-8215
Container-title:IEEE Transactions on Circuits and Systems for Video Technology
language:
Short-container-title:IEEE Trans. Circuits Syst. Video Technol.

Author:

Sheng Xiaoxiao¹^ORCID,Li Kunchang²,Shen Zhiqiang³^ORCID,Xiao Gang¹^ORCID

Affiliation:

1. Advanced Avionics and Intelligent Information Laboratory, Shanghai Jiao Tong University, Shanghai, China

2. Shenzhen Institutes of Advanced Technology (SIAT), Chinese Academy of Science, Shenzhen, China

3. Cooperative Medianet Innovation Center, Shanghai Jiao Tong University, Shanghai, China

Funder

National Natural Science Foundation of China

Science and Technology Project of Zhejiang Province

Sichuan Key Laboratory of Artificial Intelligence

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Media Technology

Link

http://xplorestaging.ieee.org/ielx7/76/10061510/09894401.pdf?arnumber=9894401

Reference60 articles.

1. HMDB: A large video database for human motion recognition

2. Dynamic normalization and relay for video action recognition;cai;Proc Adv Neural Inf Process Syst,2021

3. NUTA: Non-uniform Temporal Aggregation for Action Recognition

4. UAV-Human: A Large Benchmark for Human Behavior Understanding with Unmanned Aerial Vehicles

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1. Spatio-temporal adaptive convolution and bidirectional motion difference fusion for video action recognition;Expert Systems with Applications;2024-12

2. An efficient motion visual learning method for video action recognition;Expert Systems with Applications;2024-12

3. EPK-CLIP: External and Priori Knowledge CLIP for action recognition;Expert Systems with Applications;2024-10

4. Efficient spatio-temporal network for action recognition;Journal of Real-Time Image Processing;2024-08-23

5. CANet: Comprehensive Attention Network for video-based action recognition;Knowledge-Based Systems;2024-07

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