Awesome

PhysDreamer: Physics-Based Interaction with 3D Objects via Video Generation [website]

Useage

Setup enviroment

Install diff-gaussian-rasterization at: https://github.com/graphdeco-inria/diff-gaussian-rasterization

conda create -n physdreamer python
conda activate physdreamer

pip install -r requirements.txt

python setup.py install

Download the scenes and optimized models from Hugging Face

Download the scenes and optimized velocity and material fields from: https://huggingface.co/datasets/YunjinZhang/PhysDreamer/tree/main

Put folders of these scenes to data/physics_dreamer/xxx, e.g. data/physics_dreamer/carnations

Put pretrained models to ./models.

See dataset_dir and model_list in inference/configs/carnation.py to match the path of dataset and pretrained models.

Run inference

cd projects/inference
bash run.sh

Acknowledgement

This codebase used lots of source code from:

1. https://github.com/graphdeco-inria/gaussian-splatting
2. https://github.com/zeshunzong/warp-mpm
3. https://github.com/PingchuanMa/NCLaw

We thank the authors of these projects.

Citations

@article{zhang2024physdreamer,
    title={{PhysDreamer}: Physics-Based Interaction with 3D Objects via Video Generation},
    author={Tianyuan Zhang and Hong-Xing Yu and Rundi Wu and
            Brandon Y. Feng and Changxi Zheng and Noah Snavely and Jiajun Wu and William T. Freeman},
    journal={arxiv},
    year={2024}
}