GACA: A Gradient-Aware and Contrastive-Adaptive Learning Framework for Low-Light Image Enhancement
Author:
Affiliation:
1. College of Computer Science and Technology, Qingdao University, Qingdao, China
2. College of Computer and Data Science, Fuzhou University, Fuzhou, China
Funder
National Natural Science Foundation of China
Taishan Scholar Program of Shandong Province
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/19/10367905/10398262.pdf?arnumber=10398262
Reference67 articles.
1. Toward Fast, Flexible, and Robust Low-Light Image Enhancement
2. Low-Light Image Enhancement via Progressive-Recursive Network
3. CoCoNet: Coupled Contrastive Learning Network with Multi-level Feature Ensemble for Multi-modality Image Fusion
4. Underwater Camera: Improving Visual Perception Via Adaptive Dark Pixel Prior and Color Correction
5. Robust underwater image enhancement with cascaded multi-level sub-networks and triple attention mechanism
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