Robust Face Restoration algorithm for old photos / AI-generated faces
456.2K runs

Run time and cost

Predictions run on Nvidia T4 GPU hardware. Predictions typically complete within 19 seconds.

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


Note that 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!

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📋 License
This project is licensed under S-Lab License 1.0. Redistribution and use for non-commercial purposes should follow this license.

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

    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}