Multi-Branch and Progressive Network for Low-Light Image Enhancement-Reference-Cited by-同舟云学术

Multi-Branch and Progressive Network for Low-Light Image Enhancement

Published:2023 Issue: Volume:32 Page:2295-2308
ISSN:1057-7149
Container-title:IEEE Transactions on Image Processing
language:
Short-container-title:IEEE Trans. on Image Process.

Author:

Zhang Kaibing¹^ORCID,Yuan Cheng²^ORCID,Li Jie³,Gao Xinbo⁴^ORCID,Li Minqi²

Affiliation:

1. Shaanxi Key Laboratory of Clothing Intelligence, the School of Computer Science, and the School of Electronics and Information, Xi’an Polytechnic University, Xi’an, China

2. School of Electronics and Information, Xi’an Polytechnic University, Xi'an, China

3. Video and Image Processing System Laboratory, School of Electronic Engineering, Xidian University, Xi’an, China

4. Chongqing Key Laboratory of Image Cognition, Chongqing University of Posts and Telecommunications, Chongqing, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Textile Intelligent Equipment Information and Control Innovation Team of Shaanxi Innovation Ability Support Program

Textile Intelligent Equipment Information and Control Innovation Team of Shaanxi Innovation Team of Universities;

Natural Science Foundation of Shaanxi Province

Graduate Scientific Innovation Fund for Xi’an Polytechnic University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Graphics and Computer-Aided Design,Software

Link

http://xplorestaging.ieee.org/ielx7/83/9991910/10102793.pdf?arnumber=10102793

Reference42 articles.

1. Feedback Network for Image Super-Resolution

2. Image-to-Image Translation with Conditional Adversarial Networks

3. Attention Guided Low-Light Image Enhancement with a Large Scale Low-Light Simulation Dataset

4. Single Image Reflection Separation with Perceptual Losses

5. Convolutional LSTM network: A machine learning approach for precipitation nowcasting;shi;Proc Adv Neural Inf Process Syst,2015

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