sczhou / codeformer

Robust face restoration algorithm for old photos / AI-generated faces

  • Public
  • 32.5M runs
  • GitHub
  • Paper
  • License
Run with an API
Playground API Examples README Versions

Input

Output

Examples

View more examples

Run time and cost

This model runs on Nvidia A40 GPU hardware. Predictions typically complete within 5 seconds.

Readme

Towards Robust Blind Face Restoration with Codebook Lookup Transformer (NeurIPS 2022) Paper | Project Page | Video

visitors

This web demo is for research purposes! If you want to use our CodeFormer for permanent free, you can run the [Github Code] locally or try out [Colab Demo] instead.

  ☕️ CodeFormer is a robust face restoration algorithm for old photos or AI-generated faces. 🚀 Try CodeFormer for improved stable-diffusion generation!

If CodeFormer is helpful, please help to ⭐ the [Github Repo]. Thanks!

GitHub Stars

📋 License This project is licensed under S-Lab License 1.0. Redistribution and use for non-commercial purposes should follow this license. Note that Replicate API of CodeFormer cannot be used commercially.

📝 Citation If our work is useful for your research, please consider citing:

@inproceedings{zhou2022codeformer,
    author = {Zhou, Shangchen and Chan, Kelvin C.K. and Li, Chongyi and Loy, Chen Change},
    title = {Towards Robust Blind Face Restoration with Codebook Lookup TransFormer},
    booktitle = {NeurIPS},
    year = {2022}
}