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SMPL-X: A new, unified, 3D model of the human body

[Paper Page] [Paper] [Supp. Mat.]

SMPL-X Examples

Table of Contents

Disclaimer

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.

Description

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.

Installation

To install the model simply you can:

  1. To install from PyPi simply run:
pip install smplx
  1. Clone this repository and install it using the setup.py script:
git clone https://github.com/vchoutas/smplx
python setup.py install

Downloading the model

To download the SMPL-X go to the project website and register to get access to the downloads section.

Loading SMPL-X, SMPL-H and SMPL

SMPL and SMPL-H setup

First download the SMPL and SMPL-H models provided by the authors. Before using SMPL and SMPL-H you should follow the instructions in tools/README.md to remove the Chumpy objects from both model pkls, as well as merge the MANO parameters with SMPL-H.

Model loading

You can either use the create function from body_models or directly call the constructor for the SMPL, SMPL-H and SMPL-X model. The path to the model can either be the path to the file with the parameters or a directory with the following structure:

models
├── smpl
│   ├── SMPL_FEMALE.pkl
│   └── SMPL_MALE.pkl
├── smplh
│   ├── SMPLH_FEMALE.pkl
│   └── SMPLH_MALE.pkl
└── smplx
    ├── SMPLX_FEMALE.npz
    ├── SMPLX_FEMALE.pkl
    ├── SMPLX_MALE.npz
    ├── SMPLX_MALE.pkl
    ├── SMPLX_NEUTRAL.npz
    └── SMPLX_NEUTRAL.pkl

Example

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"

SMPL-X Examples

Citation

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}
}

    @article{SMPL:2015,
      author = {Loper, Matthew and Mahmood, Naureen and Romero, Javier and Pons-Moll, Gerard and Black, Michael J.},
      title = {{SMPL}: A Skinned Multi-Person Linear Model},
      journal = {ACM Trans. Graphics (Proc. SIGGRAPH Asia)},
      month = oct,
      number = {6},
      pages = {248:1--248:16},
      publisher = {ACM},
      volume = {34},
      year = {2015}
    }

  @article{MANO:SIGGRAPHASIA:2017,
      title = {Embodied Hands: Modeling and Capturing Hands and Bodies Together},
      author = {Romero, Javier and Tzionas, Dimitrios and Black, Michael J.},
      journal = {ACM Transactions on Graphics, (Proc. SIGGRAPH Asia)},
      volume = {36},
      number = {6},
      series = {245:1--245:17},
      month = nov,
      year = {2017},
      month_numeric = {11}
  }

Contact

For questions about our paper or code, please contact Vassilis Choutas and Georgios Pavlakos.