| pipeline_tag: unconditional-image-generation | |
| license: apache-2.0 | |
| tags: | |
| - 3D | |
| - Gaussian Splatting | |
| - GAN | |
| - Human Head Synthesis | |
| # CGS-GAN: 3D Consistent Gaussian Splatting GANs for High Resolution Human Head Synthesis | |
| CGS-GAN is a novel 3D Gaussian Splatting GAN framework designed for stable training and high-quality, 3D-consistent synthesis of human heads. It addresses the challenges of existing methods that compromise 3D consistency by relying on view-conditioning. CGS-GAN introduces a multi-view regularization technique to ensure training stability and a specialized generator architecture that facilitates efficient rendering and scaling, enabling output resolutions up to $2048^2$. | |
| - **Paper:** [CGS-GAN: 3D Consistent Gaussian Splatting GANs for High Resolution Human Head Synthesis](https://huggingface.co/papers/2505.17590) | |
| - **Project Page:** [https://fraunhoferhhi.github.io/cgs-gan/](https://fraunhoferhhi.github.io/cgs-gan/) | |
| - **Repository:** [https://github.com/fraunhoferhhi/cgs-gan](https://github.com/fraunhoferhhi/cgs-gan) | |
| ## Usage | |
| To run inference and render results, follow the setup instructions in the [official GitHub repository](https://github.com/fraunhoferhhi/cgs-gan) and use the `generate_samples.py` script with a pre-trained checkpoint: | |
| ```shell | |
| python generate_samples.py --pkl path/to/network.pkl | |
| ``` | |
| ### Optional Parameters | |
| - `--truncation_psi`: Tradeoff between quality and variety (0: quality, 1: variety). Default is `0.8`. | |
| - `--num_ids`: Number of IDs to generate (number of rows). Default is `6`. | |
| - `--radius`: Radius of the camera. Default is `2.7`. | |
| - `--seed`: Random seed for generation. Default is `42`. | |
| - `--save_dir`: Directory to save the generated results. Default is `"results"`. | |
| ## Citation | |
| Please cite our paper when using CGS-GAN in your work: | |
| ```bibtex | |
| @misc{barthel2025cgsgan, | |
| title={CGS-GAN: 3D Consistent Gaussian Splatting GANs for High Resolution Human Head Synthesis}, | |
| author={Florian Barthel and Wieland Morgenstern and Paul Hinzer and Anna Hilsmann and Peter Eisert}, | |
| year={2025}, | |
| eprint={2505.17590}, | |
| archivePrefix={arXiv}, | |
| primaryClass={cs.CV}, | |
| url={https://arxiv.org/abs/2505.17590}, | |
| } | |
| ``` |