Simulated garment dataset for virtual try-on
This repository contains the dataset used in the following papers:
-
Self-Supervised Collision Handling via Generative 3D Garment Models for Virtual Try-On (CVPR 2021) [Project website] [Video]
-
Learning-Based Animation of Clothing for Virtual Try-On (Eurographics 2019) [Project website] [Video]
Dataset
The data is generated used a modified version of ARCSim and sequences from the CMU Motion Capture Database converted to SMPL format in SURREAL. Each simulated sequence is stored as a .pkl file that contains the following data:
| Key | Description | Dimension |
|---|---|---|
| shapes | SMPL shape coefficients | [num_frames, 10] |
| poses | SMPL pose coefficients | [num_frames, 75] |
| vertices | Vertices of the simulated garment | [num_frames, num_vertices, 3] |
| faces | Faces of the garment | [num_faces, 3] |
| sequence | Sequence identifier | |
| subject | Subject identifier | |
| conf | ARCSim configuration |
Extract meshes
Requirements: python3, numpy-1.21.3
To extract the simulated garment meshes as .obj run the following script:
python extract_meshes.py tshirt/simulations/tshirt_shape00_01_01.pkl
Citation
If you find this dataset useful please cite our work:
@article {santesteban2021garmentcollisions,
journal = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
title = {{Self-Supervised Collision Handling via Generative 3D Garment Models for Virtual Try-On}},
author = {Santesteban, Igor and Thuerey, Nils and Otaduy, Miguel A and Casas, Dan},
year = {2021}
}
@article {santesteban2019virtualtryon,
journal = {Computer Graphics Forum (Proc. Eurographics)},
title = {{Learning-Based Animation of Clothing for Virtual Try-On}},
author = {Santesteban, Igor and Otaduy, Miguel A. and Casas, Dan},
year = {2019},
ISSN = {1467-8659},
DOI = {10.1111/cgf.13643}
}
