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---
license: mit
pretty_name: "Serpent"
viewer: false
---
<h1 align="center">Serpent: Scalable and Efficient Image Restoration via Multi-scale Structured State Space Models</h1>
<!-- <h3 align="center">Mohammad Shahab Sepehri, Zalan Fabian, Maryam Soltanolkotabi, Mahdi Soltanolkotabi</h3> -->
<p align="center">
<a href="https://scholar.google.com/citations?user=j2scUKoAAAAJ&hl=en">Mohammad Shahab Sepehri</a>
<a href="https://scholar.google.com/citations?user=5EKjsXQAAAAJ&hl=en">Zalan Fabian</a>
<a href="https://scholar.google.com/citations?user=narJyMAAAAAJ&hl=en">Mahdi Soltanolkotabi</a>
</p>
<p align="center">
| <a href="https://arxiv.org/abs/2403.17902">Paper</a>
|
<a href="https://github.com/AIF4S/Serpent">Github Repository</a>
|
</p>
[![License](https://img.shields.io/badge/License-MIT-blue.svg)](https://opensource.org/license/MIT)
<p align="justify" >
<strong>Serpent</strong> is a novel architecture for efficient image restoration that leverages state space models capable of modeling intricate long-range dependencies in high-resolution images with a favorable linear scaling in input dimension.
<br />
You can download our pretrained models from this repository
</p>
## Usage
You can find our code and instructions for using our pre-trained models on [our Github repository](https://github.com/AIF4S/Serpent).