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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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<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 align="center"> |
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| <a href="https://arxiv.org/abs/2403.17902">Paper</a> |
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<a href="https://github.com/AIF4S/Serpent">Github Repository</a> |
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</p> |
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[](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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You can download our pretrained models from this repository |
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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). |