DiffusionGAN3D

Project | Paper

This repository is the official implementation of DiffusionGAN3D.

DiffusionGAN3D: Boosting Text-guided 3D Generation and Domain Adaptation by Combining 3D GANs and Diffusion Priors
Biwen Lei, Kai Yu, Mengyang Feng, Miaomiao Cui, Xuansong Xie
In CVPR 2024
Alibaba Group, Hangzhou, China

DiffusionGAN3D is a novel two-stage framework, which aims to boost the performance of 3D domain adaption and text-to-avatar tasks by combining 3D generative models and diffusion priors.

Contact

If you have any questions, please contact Biwen Lei ([email protected]).

Citation

If you use our work in your research, please cite our publication:

@misc{lei2023diffusiongan3d,
      title={DiffusionGAN3D: Boosting Text-guided 3D Generation and Domain Adaption by Combining 3D GANs and Diffusion Priors}, 
      author={Biwen Lei and Kai Yu and Mengyang Feng and Miaomiao Cui and Xuansong Xie},
      year={2023},
      eprint={2312.16837},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}