[Paper Page] [Paper] [Supp. Mat.]
The original images used for the figures 1 and 2 of the paper can be found in this link. The images in the paper are used under license from gettyimages.com. We have acquired the right to use them in the publication, but redistribution is not allowed. Please follow the instructions on the given link to acquire right of usage. Our results are obtained on the 483 × 724 pixels resolution of the original images.)
SMPL-X (SMPL eXpressive) is a unified body model with shape parameters trained jointly for the face, hands and body. SMPL-X uses standard vertex based linear blend skinning with learned corrective blend shapes, has N = 10, 475 vertices and K = 54 joints, which includes joints for the neck, jaw, eyeballs and fingers. SMPL-X is defined by a function M(θ, β, ψ), where θ is the pose parameter, β the shape parameter and ψ the expression parameter.
To install the model simply you can:
- To install from PyPi simply run:
pip install smplx- Clone this repository and install it using the setup.py script:
git clone https://github.com/vchoutas/smplx
python setup.py installTo download the SMPL-X go to the project website and register to get access to the downloads section.
After installing the smplx package and downloading the model parameters you should be able to run the demo.py script to visualize the results. For this step you have to install the pyrender and trimesh packages.
python examples/demo.py --model-folder $SMPLX_FOLDER --plot-joints=True --gender="neutral"
If you find this code useful in your research then please cite:
@inproceedings{SMPL-X:2019,
title = {Expressive Body Capture: 3D Hands, Face, and Body from a Single Image},
author = {Pavlakos, Georgios and Choutas, Vasileios and Ghorbani, Nima and Bolkart, Timo and Osman, Ahmed A. A. and Tzionas, Dimitrios and Black, Michael J.},
booktitle = {Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR)},
year = {2019}
}
For questions about our paper or code, please contact Vassilis Choutas.