Added models

.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
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+hsir.model.restormer.restormer_b31_gaussian.pth filter=lfs diff=lfs merge=lfs -text
+t3sc_complex.pth filter=lfs diff=lfs merge=lfs -text
+t3sc_gaussian.pth filter=lfs diff=lfs merge=lfs -text
+grunet_official_complex.pth filter=lfs diff=lfs merge=lfs -text
+grunet_official_gaussian.pth filter=lfs diff=lfs merge=lfs -text
+hsir.model.qrnn3d.qrnn3d_gaussian.pth filter=lfs diff=lfs merge=lfs -text

README.md

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 ---
 license: mit
 ---
+
+# Description
+
+This is a collection of models supported by the hyperspectral image restoration (HSIR) toolbox, developed by Intelligent Sensing and Processing Laboratory (BIT ISP lab) at Beijing Institute of Technology.
+
+The original repository is available at:
+<https://github.com/bit-isp/HSIR>
+and models were originally downloaded at the following link:
+<https://1drv.ms/u/s!AuS3o7sEiuJnf6F4THmqDMtDCwQ?e=JpfLP3>
+
+
+# Citation
+
+To cite the original repository:
+
+```
+@misc{hsir,
+	author={Zeqiang Lai, Miaoyu Li, Ying Fu},
+	title={HSIR: Out-of-box Hyperspectral Image Restoration Toolbox},
+	year={2022},
+	url={https://github.com/bit-isp/HSIR},
+}
+```
+For each of the model please cite:
+
+- HSID-CNN
+  ```bibtex
+  @ARTICLE{yuan2019,
+    author={Q. {Yuan} and Q. {Zhang} and J. {Li} and H. {Shen} and L. {Zhang}},
+    journal={IEEE Trans. Geosci. Remote Sens.},
+    title={Hyperspectral Image Denoising Employing a Spatial-Spectral Deep Residual Convolutional Neural Network},
+    year={2019},
+    volume={57},
+    number={2},
+    pages={1205-1218},
+    month={Feb.},
+  }
+  ```
+- QRNN3D
+  ```bibtex
+  @article{wei2020QRNN3D,
+    title={3-D Quasi-Recurrent Neural Network for Hyperspectral Image Denoising},
+    author={Wei, Kaixuan and Fu, Ying and Huang, Hua},
+    journal={IEEE Transactions on Neural Networks and Learning Systems},
+    year={2020},
+    publisher={IEEE}
+  }
+  ```
+- TS3C
+  ```bibtex
+  @article{bodrito2021trainable,
+    title={A Trainable Spectral-Spatial Sparse Coding Model for Hyperspectral Image Restoration},
+    author={Bodrito, Theo and Zouaoui, Alexandre and Chanussot, Jocelyn and Mairal, Julien},
+    journal={Adv. in Neural Information Processing Systems (NeurIPS)},
+    year={2021}
+  }
+  ```
+- GRUNet
+  ```bibtex
+  @article{lai2022dphsir,
+    title = {Deep plug-and-play prior for hyperspectral image restoration},
+    journal = {Neurocomputing},
+    volume = {481},
+    pages = {281-293},
+    year = {2022},
+    issn = {0925-2312},
+    doi = {https://doi.org/10.1016/j.neucom.2022.01.057},
+    author = {Zeqiang Lai and Kaixuan Wei and Ying Fu},
+  }
+  ```
+
+- SST
+  ```bibtex
+  @inproceedings{li2023spatial,
+    title={Spatial-Spectral Transformer for Hyperspectral Image Denoising},
+    author={Li, Miaoyu and Fu, Ying and Zhang, Yulun},
+    booktitle={AAAI},
+    year={2023}
+  }
+  ```
+- SERT
+  ```bibtex
+  @inproceedings{li2023spectral,
+    title={Spectral Enhanced Rectangle Transformer for Hyperspectral Image Denoising},
+    author={Miaoyu Li and Ji Liu and Ying Fu and Yulun Zhang and Dejing Dou},
+    booktitle={CVPR},
+    year={2023}
+  }
+  ```
+- MAN
+  ```bibtex
+  @article{lai2023mixed,
+    title={Mixed Attention Network for Hyperspectral Image Denoising},
+    author={Lai, Zeqiang and Fu, Ying},
+    journal={arXiv preprint arXiv:2301.11525},
+    year={2023}
+  }
+  ```
+- HSDT
+  ```bibtex
+  @inproceedings{lai2023hsdt,
+    author = {Lai, Zeqiang and Chenggang, Yan and Fu, Ying},
+    title = {Hybrid Spectral Denoising Transformer with Guided Attention},
+    booktitle={Proceedings of the IEEE International Conference on Computer Vision},
+    year = {2023},
+  }
+  ```

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