DTCM: Joint Optimization of Dark Enhancement and Action Recognition in Videos-Reference-Cited by-同舟云学术

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DTCM: Joint Optimization of Dark Enhancement and Action Recognition in Videos

Published:2023 Issue: Volume:32 Page:3507-3520
ISSN:1057-7149
Container-title:IEEE Transactions on Image Processing
language:
Short-container-title:IEEE Trans. on Image Process.

Author:

Tu Zhigang¹^ORCID,Liu Yuanzhong¹^ORCID,Zhang Yan²,Mu Qizi³,Yuan Junsong⁴^ORCID

Affiliation:

1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China

2. Department of Clinical Laboratory, Renmin Hospital of Wuhan University, Wuhan, China

3. CHN Energy Digital Intelligence Technology Development (Beijing) Company Ltd., Beijing, China

4. Computer Science and Engineering Department, The State University of New York at Buffalo, Buffalo, NY, USA

Funder

Natural Science Fund for Distinguished Young Scholars of Hubei Province

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Graphics and Computer-Aided Design,Software

Link

http://xplorestaging.ieee.org/ielx7/83/9991910/10155640.pdf?arnumber=10155640

Reference82 articles.

1. A General Dynamic Knowledge Distillation Method for Visual Analytics

2. NTU RGB+D 120: A Large-Scale Benchmark for 3D Human Activity Understanding

3. Deep historical long short-term memory network for action recognition

4. SMAM: Self and Mutual Adaptive Matching for Skeleton-Based Few-Shot Action Recognition

5. Optical Flow in the Dark

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1. Dark-DSAR: Lightweight one-step pipeline for action recognition in dark videos;Neural Networks;2024-11

2. Uncertainty modified policy for multi-agent reinforcement learning;Applied Intelligence;2024-09-09

3. ModelNet-O: A large-scale synthetic dataset for occlusion-aware point cloud classification;Computer Vision and Image Understanding;2024-09

4. Contextual Visual and Motion Salient Fusion Framework for Action Recognition in Dark Environments;Knowledge-Based Systems;2024-09

5. Explore human parsing modality for action recognition;CAAI Transactions on Intelligence Technology;2024-08-16

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