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FPro

Seeing the Unseen: A Frequency Prompt Guided Transformer for Image Restoration

Install / Use

/learn @joshyZhou/FPro
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

Seeing the Unseen: A Frequency Prompt Guided Transformer for Image Restoration (ECCV 2024)

Hugging Face Demo visitors GitHub Stars <br>

Shihao Zhou, Jinshan Pan, Jinglei Shi, Duosheng Chen, Lishen Qu and Jufeng Yang

News

  • Jul 13, 2025: Hugging Face Demo is available now, thanks contribution of Sen
  • Jul 02, 2024: FPro has been accepted to ECCV 2024 :tada:
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Training

Derain

To train FPro on SPAD, you can run:

./train.sh Deraining/Options/Deraining_FPro_spad.yml

Dehaze

To train FPro on SOTS, you can run:

./train.sh Dehaze/Options/RealDehazing_FPro.yml

Deblur

To train FPro on GoPro, you can run:

./train.sh Motion_Deblurring/Options/Deblurring_FPro.yml

Deraindrop

To train FPro on AGAN, you can run:

./train.sh Deraining/Options/RealDeraindrop_FPro.yml

Demoire

To train FPro on TIP18, you can run:

./train.sh Demoiring/Options/RealDemoiring_FPro.yml

Evaluation

To evaluate FPro, you can refer commands in 'test.sh'

For evaluate on each dataset, you should uncomment corresponding line.

Results

Experiments are performed for different image processing tasks including, rain streak removal, raindrop removal, haze removal, motion blur removal, and moire pattern removal. Here is a summary table containing hyperlinks for easy navigation:

<table> <tr> <th align="left">Benchmark</th> <th align="center">Pretrained model</th> <th align="center">Visual Results</th> </tr> <tr> <td align="left">SPAD</td> <td align="center"><a href="https://pan.baidu.com/s/1lHWbvsFFpbvja_vEcvnpqA">(code:gd8j)</a></td> <td align="center"><a href="https://pan.baidu.com/s/1duMbd4L0rvrWvxv9wnW2eg">(code:ntgp)</a></td> </tr> <tr> <td align="left">AGAN</td> <td align="center"><a href="https://pan.baidu.com/s/1Ki2kmibr515dCJmbdlpMhQ">(code:dqml)</a></td> <td align="center"><a href="https://pan.baidu.com/s/1cPbbsNM6i5ufyzIqPJz60g">(code:ul55)</a></td> </tr> <tr> <td align="left">SOTS</td> <td align="center"><a href="https://pan.baidu.com/s/117lm0l06YW1RuFzDPLiMZA">(code:aagq)</a></td> <td align="center"><a href="https://pan.baidu.com/s/1N-ZVnL3oGRy3voJ3Fl-YtQ">(code:9ssj)</a></td> </tr> <tr> <td align="left">GoPro</td> <td align="center"><a href="https://pan.baidu.com/s/1WjEISK2AntfdYOrrMwZOZw">(code:lhds)</a></td> <td align="center"><a href="https://pan.baidu.com/s/1EkXTI968Cyu7UnKwdgymag">(code:764e)</a></td> </tr> <tr> <td align="left">TIP18</td> <td align="center"><a href="https://pan.baidu.com/s/1NPmeAIZkVz7DkLVJxuonIw">(code:l13v)</a></td> <td align="center"><a href="https://pan.baidu.com/s/1tLGRx2pvogS0Sl7fpmloNQ">(code:9und)</a></td> </tr> </table>

Citation

If you find this project useful, please consider citing:

@inproceedings{zhou_ECCV2024_FPro,
  title={Seeing the Unseen: A Frequency Prompt Guided Transformer for Image Restoration},
  author={Zhou, Shihao and Pan, Jinshan and Shi, Jinglei and Chen, Duosheng and Qu, Lishen and Yang, Jufeng},
  booktitle={ECCV},
  year={2024}
}

Acknowledgement

This code borrows heavily from Restormer.

Related Skills

View on GitHub
GitHub Stars56
CategoryDevelopment
Updated11d ago
Forks0

Languages

Python

Security Score

80/100

Audited on Mar 27, 2026

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