Vladimir Chernyy, Ivan Gerasimov, Rustam Guseynzade, Hai Le, Prateek Rajput

This repo provides the replication of paper on image restoration. The goal is to restore high-quality images from low-quality images. We utilized SwinIR (Liang et al., 2021) model based on the Swin Transformer, which consisted of three main parts:

• Shallow feature extraction
• Deep feature extraction – Composed of many residual Swin Transformer blocks (RSTB), each has several Swin Transformers layers together with a residual connection
• High-quality image reconstruction. We examined the performance of SwinIR with its default blind noises against our own synthetic noise. Moreover, we implemented the ISTA/FISTA algorithms with SwinIR as a de-noising model for non-blind deblurring problem.

This is an example of how you may give instructions on setting up your project locally. To get a local copy up and running follow these simple example steps.

1. Clone the repo

   git clone https://github.com/ctrlzet/imgrestore

Our repo follows steps mentioned in 2nd project description

• main branch consists of two directories correspoding to training and inference procedures each. This is all about replication of original paper + implication of projection layer. User required to follow a step-by-step intructions mentioned in .ipynb files located in same path.
• The first task covering research solved here.
• Finally, ISTA/FISTA algorithms stored here: 1 and 2.

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

Vladimir Chernyy - [email protected] - author of README.md

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