30 open-source projects similar to jianghaiscu/diffusion-low-light, ranked by shared indexed features. Tags may describe platforms or build tools rather than the same primary purpose. Check each project’s use case, license, and deployment requirements before treating it as a replacement.
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
Authors: Yuyang Yin, Dejia Xu, Chuangchuang Tan, Ping Liu, Yao Zhao, Yunchao Wei
Welcome! This is the official implementation of the paper "ExposureDiffusion: Learning to Expose for Low-light Image Enhancement".
By Cheuk-Yiu Chan, Wan-Chi Siu, Yuk-Hee Chan and H. Anthony Chan
[Paper](https://dl.acm.org/doi/abs/10.1145/3503161.3548135)
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~
this is the official code for the paper "Retinex-inspired Unrolling with Cooperative Prior Architecture Search for Low-light Image Enhancement"
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 repository contains the official PyTorch implementation of EFINet, a lightweight enhancement-fusion iterative network for restoring low-light images.
By Chu Zhou, Minggui Teng, Youwei Lyu, Si Li, Chao Xu, Boxin Shi
Wenhan Yang, Shiqi Wang, Yuming Fang, Yue Wang and Jiaying Liu
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
Codes for "A Dual Sensor Computational Camera for High Quality Dark Videography"
Raman Jha, Adithya Lenka, Mani Ramanagopal, Aswin Sankaranarayanan, Kaushik Mitra
1.Sichuan University, 2.Southwest Jiaotong University, 3.University of Electronic Science and Technology of China, 4.Shanghai Jiaotong University, 5.Megvii Technology
This is an implementation of the following paper.
Jie Huang+, Yajing Liu+, Feng Zhao*, Keyu Yan, Jinghao Zhang, Yukun Huang, Man Zhou, Zhiwei Xiong
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.
Yuhui Wu, Chen Pan, Guoqing Wang, Yang Yang, Jiwei Wei, Chongyi Li, Heng Tao Shen (Corresponding Author)
You can find more details here: https://li-chongyi.github.io/Proj_Zero-DCE.html. Have fun!
See URetinex-Net++. We release training code of URetinex-Net++, which share the decomposition module and unfolding module with URetinex-Net, enjoy!