Home

Awesome

3D Clothed Human Reconstruction in the Wild (ClothWild codes)

3D Clothed Human Reconstruction in the Wild,
Gyeongsik Moon*, Hyeongjin Nam*, Takaaki Shiratori, Kyoung Mu Lee (* equal contribution)
European Conference on Computer Vision (ECCV), 2022

<p align="center"> <img src="assets/front_figure.png"> </p> <p align="center"> <img src="assets/qualitative_result.png"> </p>

Installation

Quick demo

Directory

Refer to here.

Running ClothWild

Train

In the main/config.py, you can change datasets to use.

cd ${ROOT}/main
python train.py --gpu 0

Test

Place trained model at the output/model_dump and follow below.

To evaluate CD (Chamfer Distance) on 3DPW, run

cd ${ROOT}/main
python test.py --gpu 0 --test_epoch 7 --type cd

To evaluate BCC (Body-Cloth Correspondence) on MSCOCO, run

cd ${ROOT}/main
python test.py --gpu 0 --test_epoch 7 --type bcc

You can download the checkpoint trained on MSCOCO+DeepFashion2 from here.

Result

Refer to the paper's main manuscript and supplementary material for diverse qualitative results!

Chamfer Distance (CD)

<p align="center"> <img src="assets/chamfer_distance.png"> </p>

Body-Cloth Correspondence (BCC)

<p align="center"> <img src="assets/body_cloth_correspondence.png"> </p>

Reference

@InProceedings{Moon_2022_ECCV_ClothWild,  
author = {Moon, Gyeongsik and Nam, Hyeongjin and Shiratori, Takaaki and Lee, Kyoung Mu},  
title = {3D Clothed Human Reconstruction in the Wild},  
booktitle = {European Conference on Computer Vision (ECCV)},  
year = {2022}  
}