"Retinexformer: One-stage Retinex-based Transformer for Low-light Image Enhancement" (ICCV 2023) & (NTIRE 2024 Runner-Up)

[IEEE TIP] "EnlightenGAN: Deep Light Enhancement without Paired Supervision" by Yifan Jiang, Xinyu Gong, Ding Liu, Yu Cheng, Chen Fang, Xiaohui Shen, Jianchao Yang, Pan Zhou, Zhangyang Wang

Project page of the paper "Learning Multi-Scale Photo Exposure Correction" (CVPR 2021).

Python implementation of two low-light image enhancement techniques via illumination map estimation

🌕 [BMVC 2022] You Only Need 90K Parameters to Adapt Light: A Light Weight Transformer for Image Enhancement and Exposure Correction. SOTA for low light enhancement, 0.004 seconds try this for pre-processing.

[ECCV2022] "Unsupervised Night Image Enhancement: When Layer Decomposition Meets Light-Effects Suppression", https://arxiv.org/abs/2207.10564

Image-enhancement algorithms: low-light enhancement, image restoration, super-resolution reconstruction. 图像增强算法探索：低光增强、图像修复、超分辨率重建 ……

🌕 [ICCV 2021] Multitask AET with Orthogonal Tangent Regularity for Dark Object Detection. A self-supervised learning way for low-light image object detection.

[ACMMM2023] "Enhancing Visibility in Nighttime Haze Images Using Guided APSF and Gradient Adaptive Convolution", https://arxiv.org/abs/2308.01738

Official PyTorch code and dataset of the paper "Local Color Distributions Prior for Image Enhancement" [ECCV2022]

[SPL 2025] LYT-Net: Lightweight YUV Transformer-based Network for Low-Light Image Enhancement

Pytorch implementation of Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement

Project of 'TBEFN: A Two-branch Exposure-fusion Network for Low-light Image Enhancement '

LoLI-Street is a low-light image enhancement dataset for training and testing low-light image enhancement models under urban street scenes.

[Access 2020] Low-Light Image Enhancement With Regularized Illumination Optimization and Deep Noise Suppression

[2025] ModalFormer: Multimodal Transformer for Low-Light Image Enhancement

Images captured in outdoor scenes can be highly degraded due to poor lighting conditions. These images can have low dynamic ranges with high noise levels that affect the overall performance of computer vision algorithms. To make computer vision algorithms robust in low-light conditions, use low-light image enhancement to improve the visibility o…

[JON 2022] Lightweight Deep Network-Enabled Real-Time Low-Visibility Enhancement for Promoting Vessel Detection in Maritime Video Surveillance

Low light enhance for driving scene

[Sensors 2025] Enhancing Low-Light Images with Kolmogorov–Arnold Networks in Transformer Attention