https://github.com/wlydlut/C2F-DFT
[CVIU 2024] Coarse-to-Fine Mechanisms Mitigate Diffusion Limitations on Image Restoration
https://github.com/wlydlut/C2F-DFT
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[CVIU 2024] Coarse-to-Fine Mechanisms Mitigate Diffusion Limitations on Image Restoration
- Host: GitHub
- URL: https://github.com/wlydlut/C2F-DFT
- Owner: wlydlut
- Created: 2023-05-11T10:33:42.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2024-08-20T08:42:43.000Z (9 months ago)
- Last Synced: 2024-10-30T22:40:15.155Z (6 months ago)
- Language: Python
- Homepage:
- Size: 6.9 MB
- Stars: 38
- Watchers: 2
- Forks: 7
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
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- awesome-diffusion-categorized - [Code
README
# Coarse-to-Fine Mechanisms Mitigate Diffusion Limitations on Image Restoration (C2F-DFT)
Liyan Wang, Qinyu Yang, Cong Wang, Wei Wang, and Zhixun Su*
[2024-08-11] Our paper is accepted to Computer Vision and Image Understanding (CVIU).
## Coarse Training Pipeline of Diffusion Transformer Model (DFT)
## Fine Training Pipeline and Sampling Phase
## Requirements
- CUDA 10.1 (or later)
- Python 3.9 (or later)
- Pytorch 1.8.1 (or later)
- Torchvision 0.19
- OpenCV 4.7.0
- tensorboard, skimage, scipy, lmdb, tqdm, yaml, einops, natsort
## Training and Evaluation
Training and testing instructions and visualization results for Image Deraining, Image Deblurring, and Real Image Denoising are provied in the links below.
Task
Training
Testing
C2F-DFT's Visual Results
Image Deraining
Link
Link
Download
Image Deblurring
Link
Link
Download
Real Image Denoising
Link
Link
Download
## Experimental Results
Image Deraining (click to expand)
Image Deblurring (click to expand)
Real Image Denoising (click to expand)
## Citation
```
@article{WANG2024104118,
title = {Coarse-to-fine mechanisms mitigate diffusion limitations on image restoration},
journal = {Computer Vision and Image Understanding},
volume = {248},
pages = {104118},
year = {2024},
issn = {1077-3142},
}
```
## Acknowledgments
This code is based on the [BasicSR](https://github.com/xinntao/BasicSR) toolbox and [Restormer](https://github.com/swz30/Restormer), [WeatherDiffusion](https://github.com/IGITUGraz/WeatherDiffusion).