This is a resouce list for low light image enhancement

[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

Contrast Enhancement Techniques for low-light images

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

[ICCV 2023] Lighting Every Darkness in Two Pairs: A Calibration-Free Pipeline for RAW Denoising && [Arxiv 2023] Make Explicit Calibration Implicit: Calibrate Denoiser Instead of the Noise Model

Code for “MBLLEN: Low-light Image/Video Enhancement Using CNNs”, BMVC 2018.

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

[TPAMI 2023 / ACMMM 2022 Best Paper Runner-Up Award] Learnability Enhancement for Low-light Raw Denoising: Where Paired Real Data Meets Noise Modeling (a Data Perspective)

Rethinking Noise Synthesis and Modeling in Raw Denoising (ICCV2021)

[CVPR 2023] Diverse Embedding Expansion Network and Low-Light Cross-Modality Benchmark for Visible-Infrared Person Re-identification

Download and convert MIDV-500 annotations to COCO instance segmentation format

a dehaze / picture enhancement demo using ncnn

[CVPR2024]Day-Night Cross-domain Vehicle Re-identification

Low Light Image Enhancement

EventEgo3D: 3D Human Motion Capture from Egocentric Event Streams [CVPR'24]

IJCV2023 paper: Deblurring Low-Light Images with Events

The Official Implementation for paper "Chain-of-Restoration: Multi-Task Image Restoration Models are Zero-Shot Step-by-Step Universal Image Restorers".

GenISP: Neural ISP for Low-Light Machine Cognition

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

[IJCV'24] Temporally Consistent Enhancement of Low-light Videos via Spatial-Temporal Compatible Learning