Related paper and code list
This repository is the collection of low light image enhancement methods and resources.
We will focus on papers with new perspectives/tools/datasets/records.
Feel free to contribute to this list, recommend readed paper/code/resources and share your comments.
- Methods
- Datasets
- People/Groups
- [Sorted by venue and publication time]
- [Conference]
- [Journal]
- Related topics and resources
- [Image denoising]
- [Open datasets]
-
LIME: Low-light Image Enhancement viaIllumination Map Estimation [Code, Paper]
- Xiaojie Guo, Yu Li, and Haibin Ling. IEEE Transactions on image processing (TIP). 2016.
-
Learning to See in the Dark [Project, Code, Paper]
- Chen Chen, Qifeng Chen, Jia Xu and Vladlen Koltun. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018
-
Learning a Deep Single Image Contrast Enhancer from Multi-Exposure Images (SICE) [Code, Paper]
- Jianrui Cai, Shuhang Gu, Lei Zhang, IEEE TRANSACTIONS ON IMAGE PROCESSING(TIP), 2018
-
Deep Retinex Decomposition for Low-Light Enhancement (RetinexNet) [Project, Code, Paper]
- Chen Wei,Wenjing Wang,Wenhan Yang,Jiaying Liu,The British Machine Vision Conference (BMVC), 2018
-
MBLLEN: Low-light Image/Video Enhancement Using CNNs [Project, Code, Paper]
- Feifan Lv, Feng Lu, Jianhua Wu and Chongsoon Lim, BMVC,2018
-
Kindling the Darkness: a Practical Low-light Image Enhancer [Code, Paper]
- Yonghua Zhang, Jiawan Zhang, Xiaojie Guo, ACM MultiMedia(MM), 2019
-
EnlightenGAN: Deep Light Enhancement without Paired Supervision [Code, Paper]
- Yifan Jiang, Xinyu Gong, Ding Liu, Yu Cheng, Chen Fang, Xiaohui Shen, Jianchao Yang, Pan Zhou, Zhangyang Wang, arXiv, 2019
-
Getting to Know Low-light Images with The Exclusively Dark Dataset [Code, Paper]
- Yuen Peng Loh, Chee Seng Chan, CVIU, 2019
-
Underexposed Photo Enhancement Using Deep Illumination Estimation (DeepUPE) [Code, Paper]
- Ruixing Wang, Qing Zhang, Chi-Wing Fu, Xiaoyong Shen, Wei-Shi Zheng, Jiaya Jia, CVPR, 2019
-
Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement (DCE-Net) [Project, Code, Paper]
- Chunle Guo, Chongyi Li,Jichang Guo, Chen Change Loy, Junhui Hou, Sam Kwong, Runmin Cong, CVPR, 2020
- Structure-Revealing Low-Light Image Enhancement Via Robust Retinex Model [Code (p file), Paper]
- Mading Li,Jiaying Liu, Wenhan Yang, Xiaoyan Sun, Zongming Guo, TIP, 2018
- Benchmarking Low-Light Image Enhancement and Beyond, [Paper], IJCV 2021
- Semantically-guided low-light image enhancement, [Paper], PRL
- Low-light image enhancement based on multi-illuminationestimation, [Paper], Applied Intelligence
- Integrating Semantic Segmentation and Retinex Model for LowLight Image Enhancement, [Paper], MM
- Attention-Based Network For Low-Light Image Enhancement [Paper]
- Cheng Zhan, Qingsen Yan, Yu Zhu, Xianjun Li, Jinqiu Sun, Yanning Zhang, ICME,2020
- An Experiment-Based Review of Low-Light Image Enhancement Methods [Paper], IEEE Access, 2020
- Unsupervised Real-world Low-light Image Enhancement with Decoupled Networks [Paper], Arxiv, 2020
- LR3M: Robust Low-Light Enhancement via Low-Rank Regularized Retinex Model [Paper]
- Xutong Ren, Wenhan Yang, Wen-Huang Cheng, and Jiaying Liu, TIP, 2020
- Visual Perception Model for Rapid and AdaptiveLow-light Image Enhancement, [Paper], arxiv, submit to TCVST, 2020
- From Fidelity to Perceptual Quality: A Semi-Supervised Approach forLow-Light Image Enhancement [Paper], CVPR, 2020
- Learning to Restore Low-Light Images via Decomposition-and-Enhancement [Paper], CVPR, 2020
- Low Light Video Enhancement using Synthetic Data Produced with an Intermediate Domain Mapping [Paper], arxiv, ECCV, 2020
- NPE (Naturalness preserved enhancement) 84 images [Naturalness Preserved Enhancement Algorithm for Non-Uniform Illumination Images]
- LIME 10 images [LIME: Low-light Image Enhancement viaIllumination Map Estimation]
- MEF 17 images [Perceptual Quality Assessment for Multi-Exposure Image Fusion]
- DICM 64 images [Contrast Enhancement Based on Layered Difference Representation of 2D Histograms TIP 2013]
- VV [Link] 24 images
- See-in-the-Dark (SID) [Learning to See in the Dark]
- 5094 raw short exposure reference image with a corresponding long-exposure reference image.
- LOL (Low Light paired dataset) [Link]
- Single Image Contrast Enhancer (SICE) [Link]
- 589 sequences, 4413 multi-exposre images, image resolution 3000*2000-6000*4000
- DARK FACE [Link]
- 789 paired low-light/normal-light images, 9,000 unlabeled low-light images
- ExDark [Link]
- Low light text detection [Paper]
- Arbitrarily-Oriented Text Detection in Low Light Natural Scene Images [Paper] TMM 2020
- YOLO in the Dark - Domain AdaptationMethod for Merging Multiple Models [Paper] ECCV 2020
- Qifeng Chen, Intel [Homepage]
- Wenhan Yang [Homepage], Jiaying Liu, PKU [STRUCT Group Website]
- Jiaya Jia [Homepage], Xiaoyong Shen [Homepage], CUHK
- Qing Zhang [Homepage], Weishi Zheng [Homepage], Sun Yat-sen University
- Chongyi Li [Homepage], Chen Change (Cavan) Loy[Homepage], Nanyang Technological University (NTU)
- Xiejie Guo [Homepage], TianJing U
- Exploiting Deep Generative Prior for Versatile Image Restoration and Manipulation [Paper, Code], ECCV, 2020, Oral
- Microscopy Image Restoration with Deep Wiener-Kolmogorov Filters [Paper], ECCV, 2020
- Practical Deep Raw Image Denoising on Mobile Devices, [Paper], ECCV, 2020
- Training Interpretable Convolutional Neural Networks by Differentiating Class-specific Filters [Paper] ECCV, 2020, Oral
- Guided Deep Decoder: Unsupervised Image Pair Fusion [Paper, Code], ECCV, 2020
- Filter Style Transfer between Photos [Paper], ECCV, 2020
- Dual Attention Network for Scene Segmentation [Paper, Code], CVPR 2019, citing 536(30th, sep, 2020), github star 1.7k
- New Trends in Image Restoration and Enhancement workshop and challenges and video restoration and enhancement (NITRE) [2020]
- A Survey on Generative Adversarial Networks:Variants, Applications,and Training [Paper]
- Generalizing from a Few Examples: A Survey on Few-Shot Learning [Paper]
- Stanford EE367/CS448I: Computational Imaging and Display [Link]