You Can See Clearly Now !

By Xiang Chen, Yufeng Li, Yufeng Huang

1 Description

A collection of awesome low-light image enhancement methods. Papers, codes and datasets are maintained.

Atoum et al, Color-wise Attention Network for Low-light Image Enhancement. [paper][code]
Lv et al, Attention Guided Low-light Image Enhancement with a Large Scale Low-light Simulation Dataset. [paper][code]
Guo et al, Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement. [paper][code]
Wei et al, A Physics-based Noise Formation Model for Extreme Low-light Raw Denoising. [paper][code]
Fu et al, Learning an Adaptive Model for Extreme Low-light Raw Image Processing. [paper][code]
Wang et al, Extreme Low-Light Imaging with Multi-granulation Cooperative Networks. [paper][code]
Karadeniz et al, Burst Denoising of Dark Images. [paper][code]
Xiong et al, Unsupervised Real-world Low-light Image Enhancement with Decoupled Networks. [paper][code]
Liang et al, Deep Bilateral Retinex for Low-Light Image Enhancement. [paper][code]
Zhang et al, ATTENTION-BASED NETWORK FOR LOW-LIGHT IMAGE ENHANCEMENT. [paper][code]
Li et al, Visual Perception Model for Rapid and Adaptive Low-light Image Enhancement. [paper][code]
Zhang et al, Self-supervised Image Enhancement Network: Training with Low Light Images Only. [paper][code]
Xu et al, Learning to Restore Low-Light Images via Decomposition-and-Enhancement. [paper][code]

Wang et al, Underexposed Photo Enhancement using Deep Illumination Estimation. [paper][code]
Loh et al, Low-light image enhancement using Gaussian Process for features retrieval. [paper][code]
Zhang et al, Kindling the Darkness: A Practical Low-light Image Enhancer. [paper][code]
Ren et al, Low-Light Image Enhancement via a Deep Hybrid Network. [paper][code]
Jiang et al, EnlightenGAN: Deep Light Enhancement without Paired Supervision. [paper][code]
Wang et al, RDGAN: RETINEX DECOMPOSITION BASED ADVERSARIAL LEARNING FOR LOW-LIGHT ENHANCEMENT. [paper][code]

Chen et al, Learning to See in the Dark. [paper][code]
Wei et al, Deep Retinex Decomposition for Low-Light Enhancement. [paper][code]
Wang et al, GLADNet: Low-Light Enhancement Network with Global Awareness. [paper][code]
Lv et al, MBLLEN: Low-light Image/Video Enhancement Using CNNs. [paper][code]
Jiang et al, Deep Refinement Network for Natural Low-Light Image Enhancement in Symmetric Pathways. [paper][code]
Cai et al, Learning a Deep Single Image Contrast Enhancer from Multi-Exposure Images. [paper][code]

GHARBI et al, Deep Bilateral Learning for Real-Time Image Enhancement. [paper][code]
Shen et al, MSR-net:Low-light Image Enhancement Using Deep Convolutional Network. [paper][code]
Tao et al, LLCNN: A convolutional neural network for low-light image enhancement. [paper][code]
Ying et al, A Bio-Inspired Multi-Exposure Fusion Framework for Low-light Image Enhancement. [paper][code]

Lore et al, LLNet: A Deep Autoencoder approach to Natural Low-light Image Enhancement. [paper][code]
Guo et al, LIME: Low-Light Image Enhancement via Illumination Map Estimation. [paper][code]