Garment4D

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Overview

This is the codebase for our NeurIPS 2021 paper Garment4D: Garment Reconstruction from Point Cloud Sequences.

For further information, please contact Fangzhou Hong.

News

• 2021-12 Code release!
• 2021-09 Garment4D is accepted to NeurIPS 2021.

Getting Started

Please checkout the scripts folder for the training scripts. We currently support three types of garments i.e. skirts, Tshirts and Trousers. Take skirts training as an example, please run the seg_pca_skirt2.sh first for the canonical garment reconstruction and then run the seg_pca_lbs_skirt2.sh for the posed garment reconstruction.

TODO

• Instructions for setting up python environments.
• Data to run the code.
• Pre-trained models.

Citation

If you find our work useful in your research, please consider citing the following papers:

@inproceedings{
    hong2021garmentd,
    title={Garment4D: Garment Reconstruction from Point Cloud Sequences},
    author={Fangzhou Hong and Liang Pan and Zhongang Cai and Ziwei Liu},
    booktitle={Thirty-Fifth Conference on Neural Information Processing Systems},
    year={2021},
    url={https://openreview.net/forum?id=aF60hOEwHP}
}

Acknowledgments

In our implementation, we refer to the following open-source databases:

• PointNet2.PyTorch
• pygcn
• smplx