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GarVerseLOD

This repository includes the related code of GarVerseLOD.

GarVerseLOD: High-Fidelity 3D Garment Reconstruction from a Single In-the-Wild Image using a Dataset with Levels of Details

Zhongjin Luo, Haolin Liu, Chenghong Li, Wanghao Du, Zirong Jin, Wanhu Sun, Yinyu Nie, Weikai Chen, Xiaoguang Han

| Paper | Project |

Introduction

gallery

We propose a hierarchical framework to recover different levels of garment details by leveraging the garment shape and deformation priors from the GarVerseLOD dataset. Given a single clothed human image searched from Internet, our approach is capable of generating high-fidelity 3D standalone garment meshes that exhibit realistic deformation and are well-aligned with the input image.

Install

git clone https://github.com/zhongjinluo/GarVerseLOD.git
cd GarVerseLOD/
conda env create -f environment.yaml
conda activate garverselod

This system has been tested with Python 3.8.19, PyTorch 1.13.1, PyTorch3D 0.7.1 and CUDA 11.7 on Ubuntu 20.04.

Demo

To run our system, please refer to demo/README.md for instructions.

Dataset

Please refer to dataset/README.md for instructions.

Citation

@article{luo2024garverselod,
  title={GarVerseLOD: High-Fidelity 3D Garment Reconstruction from a Single In-the-Wild Image using a Dataset with Levels of Details},
  author={Luo, Zhongjin and Liu, Haolin and Li, Chenghong and Du, Wanghao and Jin, Zirong and Sun, Wanhu and Nie, Yinyu and Chen, Weikai and Han, Xiaoguang},
  journal={ACM Transactions on Graphics (TOG)},
  year={2024}
}

Acknowledgments

The code benefits from or utilizes the folowing projects. Many thanks to their contributions.