zsxkib / draggan

🐲 DragGAN 🐉 - "Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold"

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Output

Examples

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Run time and cost

This model runs on Nvidia T4 GPU hardware. Predictions typically complete within 6 minutes. The predict time for this model varies significantly based on the inputs.

Readme

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Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold

SIGGRAPH 2023 Conference Proceedings

Acknowledgement

This code is developed based on StyleGAN3. Part of the code is borrowed from StyleGAN-Human. (cheers to the community as well 🍻)

License

Acknowledgement

This code is developed based on StyleGAN3. Part of the code is borrowed from StyleGAN-Human.

(cheers to the community as well)

License

The code related to the DragGAN algorithm is licensed under CC-BY-NC. However, most of this project are available under a separate license terms: all codes used or modified from StyleGAN3 is under the Nvidia Source Code License.

Any form of use and derivative of this code must preserve the watermarking functionality showing “AI Generated”.

BibTeX

@inproceedings{pan2023draggan,
    title={Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold},
    author={Pan, Xingang and Tewari, Ayush, and Leimk{\"u}hler, Thomas and Liu, Lingjie and Meka, Abhimitra and Theobalt, Christian},
    booktitle = {ACM SIGGRAPH 2023 Conference Proceedings},
    year={2023}
}