[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).

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

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

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

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

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

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 ……

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 '

LYT-Net: Lightweight YUV Transformer-based Network for Low-Light Image Enhancement

Low light enhance for driving scene

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…

Detect and classify the vehicles in the low light using YOLO v3 pretrained model and low light image enhancement

Convolutional Denoising Autoencoder for low light image denoising

A fork of Learning to See Moving Objects in the Dark