Add model card for CGS-GAN

README.md

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+---
+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},
+}
+```