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InterDiff: Generating 3D Human-Object Interactions with Physics-Informed Diffusion

Sirui Xu  Zhengyuan Li  Yu-Xiong Wang*  Liang-Yan Gui* 
University of Illinois Urbana-Champaign
ICCV 2023

To create the environment, you can check and build according to the requirement file requirements.txt, which is based on Python 3.7.

You may also build from a detailed requirement file based on Python 3.8, which might contain redundancies,

conda env create -f environment.yml

For more information about the implementation, see interdiff/README.md.

• [2023-10-27] Release training and evaluation codes, as well as our checkpoints. Let's play with it!
• [2023-09-16] Release a demo video 📹.
• [2023-09-01] Our paper is available on the Arxiv 🎉 Code/Models are coming soon. Please stay tuned! ☕️

• Release more demos.
• Data preparation.
• Release training and evaluation (short-term) codes.
• Release checkpoints.
• Release evaluation (long-term) and optimization codes.
• Release code for visualization.

If you find our work helpful, please cite:

@inproceedings{
   xu2023interdiff,
   title={{InterDiff}: Generating 3D Human-Object Interactions with Physics-Informed Diffusion},
   author={Xu, Sirui and Li, Zhengyuan and Wang, Yu-Xiong and Gui, Liang-Yan},
   booktitle={ICCV},
   year={2023},
}

• BEHAVE: We use the BEHAVE dataset for the mesh-based interaction.
• HO-GCN: We use its presented dataset for the skeleton-based interaction.
• TEMOS: We adopt the rendering code for HOI visualization.
• MDM: We use the MDM in our work.
• STARS: We use the STARS in our work.

This code is distributed under an MIT LICENSE.

Note that our code depends on other libraries, including SMPL, SMPL-X, PyTorch3D, Hugging Face, Hydra, and uses datasets which each have their own respective licenses that must also be followed.