ReSynth Dataset
2021-10-12
The ReSynth Dataset is a synthetic dataset of 3D clothed humans in motion, created using physics based simulation. The dataset contains 24 outfits of diverse garment types, dressed on varied body shapes across both genders. All outfits are simulated using a consistent set of 20 motion sequences captured in the CAPE dataset. We provide both the simulated high-res point clouds as well as the packed data that's ready to run with the model introduced in the ICCV 2021 paper "The Power of Points for Modeling Humans in Clothing". Checkout out the dataset website for more information.
The ReSynth Dataset is a synthetic dataset of 3D clothed humans in motion, created using physics based simulation. The dataset contains 24 outfits of diverse garment types, dressed on varied body shapes across both genders. All outfits are simulated using a consistent set of 20 motion sequences captured in the CAPE dataset. We provide both the simulated high-res point clouds as well as the packed data that's ready to run with the model introduced in the ICCV 2021 paper "The Power of Points for Modeling Humans in Clothing". Checkout out the dataset website for more information.
| Author(s): | Qianli Ma, Jinlong Yang, Siyu Tang, Michael J. Black |
| Department(s): |
Perceiving Systems |
| Research Projects(s): |
Clothing Capture and Modeling |
| Publication(s): |
The Power of Points for Modeling Humans in Clothing
|
| Authors: | Qianli Ma, Jinlong Yang, Siyu Tang, Michael J. Black |
| Release Date: | 2021-10-12 |
| External Link: | https://pop.is.tue.mpg.de/ |
