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- license: mit
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+ license: mit
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+ pretty_name: "Serpent"
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+ viewer: false
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+ ---
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+ <h1 align="center">Serpent: Scalable and Efficient Image Restoration via Multi-scale Structured State Space Models</h1>
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+ <!-- <h3 align="center">Mohammad Shahab Sepehri, Zalan Fabian, Maryam Soltanolkotabi, Mahdi Soltanolkotabi</h3> -->
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+
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+ <p align="center">
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+ <a href="https://scholar.google.com/citations?user=j2scUKoAAAAJ&hl=en">Mohammad Shahab Sepehri</a>
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+ <a href="https://scholar.google.com/citations?user=5EKjsXQAAAAJ&hl=en">Zalan Fabian</a>
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+ <a href="https://scholar.google.com/citations?user=narJyMAAAAAJ&hl=en">Mahdi Soltanolkotabi</a>
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+ </p>
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+
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+ <p align="center">
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+ | <a href="https://arxiv.org/abs/2403.17902">Paper</a>
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+ |
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+ <a href="https://github.com/AIF4S/Serpent">Github Repository</a>
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+ |
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+ </p>
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+
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+
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+ [![License](https://img.shields.io/badge/License-MIT-blue.svg)](https://opensource.org/license/MIT)
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+ <p align="justify" >
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+ <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.
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+ <br />
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+ You can download our pretrained models from this repository
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+ </p>
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+
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+ ## Usage
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+ You can find our code and instructions for using our pre-trained models on [our Github repository](https://github.com/AIF4S/Serpent).