Low-light Enhancement暗光图像增强论文整理-

github代码都放后面了，没有就是找不到代码

近年论文

Guo, Xiaojie et al. “LIME: Low-Light Image Enhancement via Illumination Map Estimation.”IEEE Transactions on Image Processing26 (): 982-993./estija/LIMEFan, Minhao et al. “Integrating Semantic Segmentation and Retinex Model for Low-Light Image Enhancement.”Proceedings of the 28th ACM International Conference on Multimedia()Xu, Ke et al. “Learning to Restore Low-Light Images via Decomposition-and-Enhancement.” IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)(): 2278-2287.Yang, W. et al. “Sparse Gradient Regularized Deep Retinex Network for Robust Low-Light Image Enhancement.”IEEE Transactions on Image Processing30 (): 2072-2086.Ren, Xutong et al. “LR3M: Robust Low-Light Enhancement via Low-Rank Regularized Retinex Model.”IEEE Transactions on Image Processing29 (): 5862-5876.Jiang, Yifan et al. “EnlightenGAN: Deep Light Enhancement Without Paired Supervision.”IEEE Transactions on Image Processing30 (): 2340-2349.Ren, W. et al. “Low-Light Image Enhancement via a Deep Hybrid Network.”IEEE Transactions on Image Processing28 (): 4364-4375. ./file/d/1WYQd5z9NXW-IOWLSH3w70t3XnLUAHnAZ/viewLi, Mading et al. “Structure-Revealing Low-Light Image Enhancement Via Robust Retinex Model.”IEEE Transactions on Image Processing27 (): 2828-2841.Fu, Gang et al. “A Hybrid L2 −LP Variational Model For Single Low-Light Image Enhancement With Bright Channel Prior.” IEEE International Conference on Image Processing (ICIP)(): 1925-1929.Loh, Y. et al. “Low-light image enhancement using Gaussian Process for features retrieval.”Signal Process. Image Commun.74 (): 175-190. /cs-chan/Exclusively-Dark-Image-Dataset/tree/master/SPICLi, Chongyi et al. “NuI-Go: Recursive Non-Local Encoder-Decoder Network for Retinal Image Non-Uniform Illumination Removal.”Proceedings of the 28th ACM International Conference on Multimedia()Zhang, Yonghua et al. “Kindling the Darkness: A Practical Low-light Image Enhancer.”Proceedings of the 27th ACM International Conference on Multimedia()Lamba, Mohit et al. “Towards Fast and Light-Weight Restoration of Dark Images.”ArXivabs/.14133 ()[code]Chen, Chen et al. “Learning to See in the Dark.” IEEE/CVF Conference on Computer Vision and Pattern Recognition(): 3291-3300.[code][code-pytorch]Wei, Chen et al. “Deep Retinex Decomposition for Low-Light Enhancement.”BMVC().[code][code-pytorch]Gharbi, Michaël et al. “Deep bilateral learning for real-time image enhancement.”ACM Transactions on Graphics (TOG)36 (): 1 - 12.[code]Wang, R. et al. “Underexposed Photo Enhancement Using Deep Illumination Estimation.” IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)(): 6842-6850.[code (only test)]Parihar, A. et al. “A Comparative Analysis of Deep Learning based Approaches for Low-Light Image Enhancement.” 5th IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE)(): 1-5.[code]Zhang, Yonghua et al. “Kindling the Darkness: A Practical Low-light Image Enhancer.”Proceedings of the 27th ACM International Conference on Multimedia(). [code]Wei, Kaixuan et al. “A Physics-Based Noise Formation Model for Extreme Low-Light Raw Denoising.” IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)(): 2755-2764.[ELD dataset] [paper][Code]Wang, Junyi et al. “RDGAN: Retinex Decomposition Based Adversarial Learning for Low-Light Enhancement.” IEEE International Conference on Multimedia and Expo (ICME)(): 1186-1191.[code]

半监督无监督（WSL）、无需成对数据（Unpaired）

Yang, W. et al. “From Fidelity to Perceptual Quality: A Semi-Supervised Approach for Low-Light Image Enhancement.” IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)(): 3060-3069.（Unpaired or WSL）Li, Chongyi et al. “Learning to Enhance Low-Light Image via Zero-Reference Deep Curve Estimation.”IEEE transactions on pattern analysis and machine intelligencePP ()（Unpaired or WSL）Lee, Hunsang et al. “Unsupervised Low-Light Image Enhancement Using Bright Channel Prior.”IEEE Signal Processing Letters27 (): 251-255.（Unpaired or WSL）Xiong, Wei et al. “Unsupervised Real-world Low-light Image Enhancement with Decoupled Networks.”ArXivabs/.02818 ()（Unpaired or WSL）Qu, Yangyang et al. “LEUGAN: Low-Light Image Enhancement by Unsupervised Generative Attentional Networks.”ArXivabs/.13322 ()（Unpaired or WSL）Zhang, Y. et al. “Self-supervised Image Enhancement Network: Training with Low Light Images Only.”ArXivabs/2002.11300 ()（Unpaired or WSL）/hitzhangyu/Self-supervised-Image-Enhancement-Network-Training-With-Low-Light-Images-OnlyLi, Chongyi et al. “Flexible Piecewise Curves Estimation for Photo Enhancement.”ArXivabs/.13412 ()（Unpaired or WSL）Jiang, Yifan et al. “EnlightenGAN: Deep Light Enhancement Without Paired Supervision.”IEEE Transactions on Image Processing30 (): 2340-2349.（Unpaired or WSL）/VITA-Group/EnlightenGANGuo, C. et al. “Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement.” IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)(): 1777-1786./Li-Chongyi/Zero-DCE

数据榜单

/task/low-light-image-enhancement