# VQGAN-Compression

**Repository Path**: ATM006/VQGAN-Compression

## Basic Information

- **Project Name**: VQGAN-Compression
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: add-UIGC
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2025-01-23
- **Last Updated**: 2025-01-23

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Introduction
Official Pytorch implementation for image compression based on VQGAN model includes:
* Finetuned-GAN:[Extreme Image Compression using Fine-tuned VQGAN Models](https://ieeexplore.ieee.org/document/10533792), DCC 2024, in [this folder](./Finetuned-VQGAN)
* UIGC:[Unifying Generation and Compression: Ultra-low bitrate Image Coding Via Multi-stage Transformer](https://ieeexplore.ieee.org/abstract/document/10687549), ICME 2024， in [this floder](./UIGC)

# :heart: Acknowledgement
The implementation is based on [VQGAN](https://github.com/CompVis/taming-transformers).

# :clipboard: Citation
If you find this work useful for your research, please cite:

```
@inproceedings{mao2024extreme,
  title={Extreme image compression using fine-tuned vqgans},
  author={Mao, Qi and Yang, Tinghan and Zhang, Yinuo and Wang, Zijian and Wang, Meng and Wang, Shiqi and Jin, Libiao and Ma, Siwei},
  booktitle={2024 Data Compression Conference (DCC)},
  pages={203--212},
  year={2024},
  organization={IEEE}
}

@inproceedings{xue2024unifying,
  title={Unifying Generation and Compression: Ultra-low bitrate Image Coding Via Multi-stage Transformer},
  author={Xue, Naifu and Mao, Qi and Wang, Zijian and Zhang, Yuan and Ma, Siwei},
  booktitle={2024 IEEE International Conference on Multimedia and Expo (ICME)}, 
  pages={1-6},
  year={2024}，
  organization={IEEE}
}
```