| --- |
| license: cc-by-nc-sa-4.0 |
| tags: |
| - gan |
| - image-generation |
| - pytorch |
| pipeline_tag: unconditional-image-generation |
| --- |
| |
| # R3GAN: FFHQ 64×64 |
|
|
| The unconditional R3GAN generator for FFHQ at 64×64, from the NeurIPS 2024 paper |
| [The GAN is dead; long live the GAN! A Modern GAN Baseline](https://arxiv.org/abs/2501.05441) |
| (the proposed configuration, config E). |
|
|
| | | | |
| |---|---| |
| | Dataset | FFHQ (Flickr-Faces-HQ) | |
| | Resolution | 64×64 | |
| | Conditioning | unconditional | |
| | FID (50k samples) | 1.95, as reported in the paper | |
| | File | `network-snapshot-final.pkl`: the final training snapshot; its `G_ema` network is the generator | |
| | Code | https://github.com/brownvc/R3GAN | |
| | Licence | [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/) | |
|
|
| ## Generating images |
|
|
| ``` |
| git clone https://github.com/brownvc/R3GAN && cd R3GAN |
| python gen_images.py --seeds=0-7 --outdir=out \ |
| --network=https://huggingface.co/brownvc/R3GAN-FFHQ-64x64/resolve/main/network-snapshot-final.pkl |
| ``` |
|
|
| The code requires the same packages as the official StyleGAN3 repository. |
|
|
| ## Intended use and limitations |
|
|
| The model is intended for research on generative models. It reproduces the statistics of its training data, |
| FFHQ (70,000 face images from Flickr), including the demographics and photographic conventions of those faces. Do not use it to create deceptive content or content that could cause harm. |
|
|
| ## Licence |
|
|
| The weights are released under [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/). The code that runs them is a separate work: the |
| `R3GAN/` directory of the GitHub repository is under the MIT licence, and the rest of the repository, which derives |
| from StyleGAN3, is under NVIDIA's Source Code License. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @inproceedings{huang2024the, |
| title={The {GAN} is dead; long live the {GAN}! A Modern {GAN} Baseline}, |
| author={Nick Huang and Aaron Gokaslan and Volodymyr Kuleshov and James Tompkin}, |
| booktitle={The Thirty-eighth Annual Conference on Neural Information Processing Systems}, |
| year={2024}, |
| url={https://openreview.net/forum?id=OrtN9hPP7V} |
| } |
| ``` |
|
|
| ## Acknowledgements |
|
|
| Brown University and Cornell University. Nick Huang was supported by a Brown University Division of Research Seed |
| Award, James Tompkin by NSF CAREER 2144956, and Volodymyr Kuleshov by NSF CAREER 2145577 and NIH MIRA 1R35GM15124301. |
| Compute was provided by Databricks Mosaic Research. |
|
|
