IOU-NB/SLURPP

<h1 align="center">SLURPP Single-Step Latent Diffusion Underwater Restoration</h1>

<p align="center"> </a> <a title="Website" href="https://tianfwang.github.io/slurpp/" target="blank" rel="noopener noreferrer" style="display: inline-block;"> <img src="https://img.shields.io/badge/%E2%99%A5%20Project%20-Website-blue" alt="Website"> </a> <a title="arXiv" href="https://arxiv.org/abs/2507.07878" target="blank" rel="noopener noreferrer" style="display: inline-block;"> <img src="https://img.shields.io/badge/%F0%9F%93%84%20Read%20-Paper-AF3436" alt="arXiv"> </a> <a title="Github" href="https://github.com/kongdai123/SLURPP" target="_blank" rel="noopener noreferrer" style="display: inline-block;"> <img src="https://img.shields.io/github/stars/kongdai123/SLURPP?label=GitHub%20%E2%98%85&logo=github&color=C8C" alt="Github">

<a title="License" href="https://www.apache.org/licenses/LICENSE-2.0" target="_blank" rel="noopener noreferrer" style="display: inline-block;"> <img src="https://img.shields.io/badge/License-Apache--2.0-929292" alt="License"> </a> </p>

This is a model card for the slurpp model for underwater image restoration and water medium estimation from a single image. The model is fine-tuned from both stable-diffusion-2 model and marigold-depth-v1-0 model.

This model is based on the paper:

Jiayi Wu, Tianfu Wang, Md Abu Bakr Siddique, Md Jahidul Islam, Cornelia Fermuller, Yiannis Aloimonos, Christopher A. Metzler "Single-Step Latent Diffusion Underwater Restoration," IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025

Using the model

Please follow the inference script in the github repo.

Model Details

• —Developed by: Jiayi Wu, Tianfu Wang, Md Abu Bakr Siddique, Md Jahidul Islam, Cornelia Fermuller, Yiannis Aloimonos, Christopher A. Metzler.
• —Model type: Diffusion-based single image underwater restoration and water medium prediction
• —Language: English.
• —License: Apache License License Version 2.0.
• —Model Description: Given an input underwater image, our single-step latent diffusion method SLURPP jointly predicts the clear image, and the per-pixel underwater medium parameters, specifically the backscattering and transmission parameters.
• —Steps and scheduler: Only one step is required with this model using trailing DDIM scheduler
• —Outputs:
• —Clear: The predicted clear image
• —Transmission/Illuminaiton: The ammount of attenuation experienced by each object in the scene
• —Backscattering: The amount additive light from illumination (ambient sunlight or artificial lights) that is scattered by the water volume
• —Resources for more information: Project Website, Paper, Code.
• —Cite as:

@article{wu2025single,
  title={Single-Step Latent Diffusion for Underwater Image Restoration},
  author={Wu, Jiayi and Wang, Tianfu and Siddique, Md Abu Bakr and Islam, Md Jahidul and Fermuller, Cornelia and Aloimonos, Yiannis and Metzler, Christopher A},
  journal={arXiv preprint arXiv:2507.07878},
  year={2025}
}