Projects sharing features with Reti Diff

Bolun Cai, Xianming Xu, Kailing Guo, Kui Jia, Bin Hu, Dacheng Tao

By Cheuk-Yiu Chan, Wan-Chi Siu, Yuk-Hee Chan and H. Anthony Chan

FG 2018 FOR-LQ workshop GLADNet

2023.12.15: Our new work Aleth-NeRF: Illumination Adaptive NeRF with Concealing Field Assumption has been accepted by AAAI 2024, please refer (here) if you interest in NeRF under low-light~

Codes for "A Dual Sensor Computational Camera for High Quality Dark Videography"

This is a pytorch project for the paper SNR-aware Low-Light Image Enhancement by Xiaogang Xu, Ruixing Wang, Chi-Wing Fu, and Jiaya Jia presented at CVPR2022.

This is an implementation of the following paper.

This is a MATLAB implementation of the paper, "LIME: Low-Light Image Enhancement via Illumination Map Estimation". It was done as a course project for Digital Image Processing (ECN-316), under the guidance of Prof. Saumik Bhattacharya.

Siggraph 2017

By Chu Zhou, Minggui Teng, Youwei Lyu, Si Li, Chao Xu, Boxin Shi

This repo is the official implementation of ICCV2021 paper "Adaptive Unfolding Total Variation Network for Low-Light Image Enhancement". For more details, please see our paper.

HDR Video Reconstruction: A Coarse-to-fine Network and A Real-world Benchmark Dataset (ICCV 2021) Guanying Chen, Chaofeng Chen, Shi Guo, Zhetong Liang, Kwan-Yee K. Wong, Lei Zhang

The implementation of CVPR 2023 paper "Physics-Guided ISO-Dependent Sensor Noise Modeling for Extreme Low-Light Photography" Paper" and its supplementary materials "supplementary materials".

Without denoise: Self-supervised Image Enhancement Network: Training With Low Light Images Only paper

Learning Image-adaptive 3D Lookup Tables for High Performance Photo Enhancement in Real-time

Wenhan Yang, Shiqi Wang, Yuming Fang, Yue Wang and Jiaying Liu

1.Sichuan University, 2.Megvii Technology, 3.University of Electronic Science and Technology of China

We use Retinexformer as an example to quickly verify the effect of GT-mean loss.

This project is a deep learning computer vision implementation focused on low-light image restoration. It uses a neural network to process raw sensor data, mapping underexposed images to well-exposed versions to improve visibility and restore natural colors. The implementation is based on CVPR 2018 research and utilizes TensorFlow to execute the computational graph. It employs a convolutional neural network and pixel-wise regression to reconstruct scene lighting directly from unprocessed raw image data. The project includes a framework for supervised pair learning, where models are trained u

Jie Huang+, Yajing Liu+, Feng Zhao*, Keyu Yan, Jinghao Zhang, Yukun Huang, Man Zhou, Zhiwei Xiong

This repository contains the official PyTorch implementation of EFINet, a lightweight enhancement-fusion iterative network for restoring low-light images.

By Cheuk-Yiu Chan, Wan-Chi Siu, Yuk-Hee Chan and H. Anthony Chan