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This repo is official PyTorch implementation of Disco4D: Disentangled 4D Human Generation and Animation from a Single Image (CVPR2025).
Refer to install.md
Prepare the dataset:
python lib/dataset/process_4ddress.pyImage-to-3D:
### Generate avatar from image
sh run_img_synthesis.sh
# ### Animate avatar
sh run_animate.sh
# ### Edit avatar
sh run_edit.sh Video-to-4D:
### Generate avatar from 4D-Dress clips
sh run_video_synthesis.sh This work is built on many amazing research works and open-source projects, thanks a lot to all the authors for sharing!
- splattingavatar
- gaussian-grouping
- dreamgaussian
- gaussian-splatting and diff-gaussian-rasterization
- threestudio
- nvdiffrast
- dearpygui
If you find our work useful for your research, please consider citing the paper:
@inproceedings{
title={Disco4D: Disentangled 4D Human Generation and Animation from a Single Image},
author={Pang, Hui En and Liu, Shuai and Cai, Zhongang and Yang, Lei and Zhang, Tianwei and Liu, Ziwei},
booktitle={CVPR},
year={2025}
}
Distributed under the S-Lab License. See LICENSE for more information.
This research/project is supported by the National Research Foundation, Singapore under its AI Singapore Programme. This study is also supported by the Ministry of Education, Singapore, under its MOE AcRF Tier 2 (MOE-T2EP20221-0012), NTU NAP, and under the RIE2020 Industry Alignment Fund – Industry Collaboration Projects (IAF-ICP) Funding Initiative, as well as cash and in-kind contribution from the industry partner(s). We sincerely thank the anonymous reviewers for their valuable comments on this paper.
