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CASSI-Self-Supervised
This repository contains the codes for paper Self-supervised Neural Networks for Spectral Snapshot Compressive Imaging (ICCV (2021)) by Ziyi Meng, Zhenming Yu, KunXu, Xin Yuan. [pdf]
Overviewer
This repository uses a self-supervised neural networks to solve the reconstruction problem of snapshot compressive imaging (SCI), which uses a two-dimensional (2D) detector to capture a high-dimensional (usually 3D) data-cube in a compressed manner. This source code provides the reconstruction of 10 synthetic data originally used in TSA-Net paper. So far this version of code only includes the PnP-DIP for the synthetic data.
Results
<p align="center"> <img src="Data/Image/Fig1.png" width="600"> </p> Fig. 1 Reconstructed synthetic data (sRGB) by 8 algorithms. We show the reconstructed spectral curves on selected regions to compare the spectral accuracy of different algorithms.Usage
Download the CASSI-Self-Supervised repository and model file
- Requirements are Python 3 and Pytorch 1.6
- Download this repository via git
- Run main.py or main.ipynb to do reconstruction of one scene.
Citation
@article{meng2021self,
title={Self-supervised Neural Networks for Spectral Snapshot Compressive Imaging},
author={Meng, Ziyi and Yu, Zhenming and Xu, Kun and Yuan, Xin},
journal={arXiv preprint arXiv:2108.12654},
year={2021}
}
Contact
Ziyi Meng, Email: mengziyi64@163.com
Xin Yuan, Westlake University, Email: xyuan@westlake.edu.cn