Bayesian-Differentiable-Physics-for-Cloth-Digitalization

Our CVPR 2024 paper 'Bayesian Differentiable Physics for Cloth Digitalization'

Needed Compilers and Libraries

• GCC 9.5.0 (or MSVC 19.29.30139)
• CUDA 11.3
• Python 3.8.13
• PyTorch 1.12.1
• Kaolin 0.12.0
• Alglib 3.17.0
• Boost 1.75
• Eigen 3.3.9

How to install

1. Install GCC and CUDA, and confirm their environment variables are set correctly.
2. Install Python (Recommond to use Anaconda to create a new environment).
3. Install Pytorch and Kaolin with following their official documentations.
4. Download Alglib, Boost, and Eigen to a diretory you like.
5. Change the Setup.py to make sure the paths are set correctly, i.e. INCLUDE_DIR.append(...).
6. Run python setup.py install.
7. Finally, you can confirm our simulator has been successfully installed by executing the following commonds in prompt:

-> python
-> import pytorch
-> import diffsim

Cusick Drape Dataset

The data are available in the .\data...

More data will be uploaded soon.

Authors

Authors Deshan Gong, Ningtao Mao and He Wang

Deshan Gong, scdg@leeds.ac.uk

He Wang, he_wang@@ucl.ac.uk, Personal website

Project Webpage: https://drhewang.com/pages/BDP.html

Citation (Bibtex)

Please cite our paper if you find it useful:

@InProceedings{Gong_Bayesian_2024,
author={Deshan Gong, Ningtao Mao and He Wang},
booktitle={The Conference on Computer Vision and Pattern Recognition (CVPR)},
title={Bayesian Differentiable Physics for Cloth Digitalization},
year={2024}}