Purpose: We aim to provide a summary of diffusion model-based image processing, including restoration, enhancement, coding, and quality assessment. More papers will be summarized.
Xin Li, Yulin Ren, Xin Jin, Cuiling Lan, Xingrui Wang, Wenjun Zeng, Xinchao Wang, Zhibo Chen
University of Science and Technology of China (USTC), National University of Singapore (NUS), Microsoft Research Asia (MSRA), Eastern Institute of Technology (EIT)
Brief intro: The survey for diffusion model-based IR has been released.
:bookmark: News!!!
- [x] 2023-09-19: Updated new related works before 15/09/2023 in this GitHub.
- [x] 2023-11-24: Updated new related works before 10/11/2023 in this GitHub.
- [x] 2023-12-25: Updated new related works before 25/12/2023 in this GitHub.
- [x] 2024-01-25: Updated new related works before 25/01/2024 in this GitHub.
- [x] 2024-03-25: Updated new related works before 25/03/2024 in this GitHub.
- [x] 2024-04-25: Updated new related works before 25/04/2024 in this GitHub.
- [x] 2024-06-25: Updated new related works before 25/06/2024 in this GitHub.
- [x] 2024-08-25: Updated new related works before 25/08/2024 in this GitHub.
- [ ] 2024-10-25: Updated new related works before 25/10/2024 in this GitHub.
📌 About new works. If you want to incorporate your studies (e.g., the link of paper or project) on diffusion model-based image processing in this repository. Welcome to raise an issue or email us. We will incorporate it into this repository and our survey report as soon as possible.
🌟 Features
- [x] Survey for diffusion model-based Image Restoration (Arxiv version is released)
- [x] Summary for diffusion model-based Image/Video Compression
- [x] Summary for diffusion model-based Quality Assessment
Diffusion model-based Image Restoration/Enhancement
Table of contents
Image Super-Resolution
Image Restoration
Image Inpainting
Image Shadow Removal
Image Denoising
Image Dehazing
Image Deblurring
Medical Restoration (MRI,CT)
Low-Light Enchancement
Other tasks
Benchmark Datasets
Dataset |
Task |
Usage |
Year |
DIV2K |
Image Super-resolution |
Training,Testing |
2017 |
Flickr2K |
Image Super-resolution |
Training |
2017 |
Set5 |
Image Super-resolution |
Testing |
2012 |
Set14 |
Image Super-resolution |
Testing |
2012 |
BSD100 |
Image Super-resolution |
Testing |
2012 |
Manga109 |
Image Super-resolution |
Testing |
2015 |
Urban100 |
Image Super-resolution |
Testing |
2015 |
OST300 |
Image Super-resolution |
Testing |
2018 |
DIV8K |
Image Super-resolution |
Training,Testing |
2019 |
RealSR |
Image Super-resolution |
Training,Testing |
2019 |
DRealSR |
Image Super-resolution |
Training,Testing |
2020 |
GoPro |
Image Deblurring |
Training,Testing |
2017 |
HIDE |
Image Deblurring |
Training,Testing |
2019 |
RealBlur |
Image Deblurring |
Training,Testing |
2020 |
Kodak |
Image Denoising |
Testing |
1999 |
CBSD68 |
Image Denoising |
Testing |
2001 |
McMaster |
Image Denoising |
Testing |
2011 |
ImageNet |
Image Classification |
Training,Testing |
2010 |
ImageNet1k |
Image Classification |
Testing |
2020 |
LSUN |
Image Classification |
Training,Testing |
2015 |
Places365 |
Image Classification |
Training,Testing |
2019 |
LFW |
Face Generation |
Training |
2008 |
FFHQ |
Face Generation |
Training |
2019 |
Celeba-HQ |
Face Generation |
Training |
2018 |
AFHQ |
Face Generation |
Training |
2020 |
CelebA |
Face Generation |
Training |
2015 |
ISTD |
Image Shadow Removal |
Training,Testing |
2018 |
SRD |
Image Shadow Removal |
Training,Testing |
2017 |
CSD |
Image Desnowing |
Training,Testing |
2021 |
Snow100k |
Image Desnowing |
Training,Testing |
2017 |
SRRS |
Image Desnowing |
Training,Testing |
2020 |
RainDrop |
Image Deraining |
Training |
2018 |
RainDropClarity |
Image Deraining |
Training,Testing |
2024 |
Outdoor-Rain |
Image Deraining |
Training,Testing |
2019 |
DDN-data |
Image Deraining |
Training,Testing |
2017 |
SPA-data |
Image Deraining |
Training,Testing |
2019 |
Rain100H |
Image Deraining |
Training,Testing |
2017 |
Rain100L |
Image Deraining |
Training,Testing |
2017 |
Haze-4K |
Image Dehazing |
Training |
2021 |
Dense-Haze |
Image Dehazing |
Training |
2019 |
RESIDE |
Image Dehazing |
Training |
2019 |
Diffusion model-based Image/Video Compression
Diffusion model-based Image/Video quality assessment
Cite US
If this work is helpful to you, we expect you can cite this work and star this repo. Thanks.
@article{li2023diffusion,
title={Diffusion Models for Image Restoration and Enhancement--A Comprehensive Survey},
author={Li, Xin and Ren, Yulin and Jin, Xin and Lan, Cuiling and Wang, Xingrui and Zeng, Wenjun and Wang, Xinchao and Chen, Zhibo},
journal={arXiv preprint arXiv:2308.09388},
year={2023}
}