Dual-Recommendation Disentanglement Network for View Fuzz in Action Recognition-Reference-Cited by-同舟云学术

Dual-Recommendation Disentanglement Network for View Fuzz in Action Recognition

Published:2023 Issue: Volume:32 Page:2719-2733
ISSN:1057-7149
Container-title:IEEE Transactions on Image Processing
language:
Short-container-title:IEEE Trans. on Image Process.

Author:

Liu Wenxuan¹^ORCID,Zhong Xian²^ORCID,Zhou Zhuo¹^ORCID,Jiang Kui³^ORCID,Wang Zheng⁴^ORCID,Lin Chia-Wen⁵^ORCID

Affiliation:

1. School of Computer Science and Artificial Intelligence, Wuhan University of Technology, Wuhan, China

2. Hubei Key Laboratory of Transportation Internet of Things, School of Computer Science and Artificial Intelligence, Wuhan University of Technology, Wuhan, China

3. School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China

4. School of Computer Science, Wuhan University, Wuhan, China

5. Department of Electrical Engineering, National Tsing Hua University, Hsinchu, Taiwan

Funder

National Natural Science Foundation of China

Department of Science and Technology, Hubei Provincial People’s Government

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Graphics and Computer-Aided Design,Software

Link

http://xplorestaging.ieee.org/ielx7/83/9991910/10122859.pdf?arnumber=10122859

Reference70 articles.

1. End-to-End Learning of Motion Representation for Video Understanding

2. Adam: A method for stochastic optimization;kingma;Proc Int Conf Learn Represent,2015

3. Rainy WCity: A Real Rainfall Dataset with Diverse Conditions for Semantic Driving Scene Understanding

4. Action Recognition from Arbitrary Views using 3D Exemplars

5. Learning Spatiotemporal Features with 3D Convolutional Networks

Cited by 9 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. Dynamic and static mutual fitting for action recognition;Pattern Recognition;2025-01

2. Converting Artificial Neural Networks to Ultralow-Latency Spiking Neural Networks for Action Recognition;IEEE Transactions on Cognitive and Developmental Systems;2024-08

3. Token-disentangling Mutual Transformer for multimodal emotion recognition;Engineering Applications of Artificial Intelligence;2024-07

4. Fragrant: frequency-auxiliary guided relational attention network for low-light action recognition;The Visual Computer;2024-05-14

5. Global Shapes and Salient Joints Features Learning for Skeleton-Based Action Recognition;IEEE Signal Processing Letters;2024