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Software Copyright License for non-commercial scientific research purposes. Please read carefully the following terms and conditions and any accompanying documentation before you download and/or use the ExPose data, model and software, (the "Data & Software"), including 3D meshes, images, videos, textures, software, scripts, and animations. By downloading and/or using the Data & Software (including downloading, cloning, installing, and any other use of the corresponding github repository), you acknowledge that you have read these terms and conditions, understand them, and agree to be bound by them. If you do not agree with these terms and conditions, you must not download and/or use the Data & Software. Any infringement of the terms of this agreement will automatically terminate your rights under this License
STAR - Sparse Trained Articulated Human Body Regressor is a generateive 3D human body model, that is designed to be a drop in replacement to the widely used SMPL model.
STAR trained on largest dataset of more than 10,000 human body scans, with a learned set of sparse spatially local pose corrective
blend shapes. In the Figure below, a single joint movement only influence a sparse set of the model vertices. The mesh vertices in
gray are not affected by the joint movement, in contrast to SMPL.
STAR is publicly avaiable with the full 300 principal component
shape space for research purposes from our [https://star.is.tue.mpg.de/]
For more details, please see our ECCV paper STAR: Sparse Trained Articulated Human Body Regressor.
This repository contains the model loader in the following frameworks:
- A PyTorch.
- A Tensorflow 2.0.
- A Chumpy.
Code tested on Python 3.69, CUDA 10.1, CuDNN 7.6.5 and PyTorch 1.6.0, Tensorflow 2.3 , Chumpy 0.69 on Ubuntu 18.04
STAR is designed to be a drop in replacement for SMPL, similar to SMPL it is parameterised with pose and shape parameters.
If you find this Model & Software useful in your research we would kindly ask you to cite:
@inproceedings{STAR:ECCV:2020,
title = {STAR: Sparse Trained Articulated Human Body Regressor},
author = {Ahmed A. A. Osman, Timo Bolkart, Michael J. Black},
booktitle = {European Conference on Computer Vision (ECCV) },
month = aug,
year = {2020},
month_numeric = {8}
}
We thank Naureen M. Mahmood, Talha Zaman, Nikos Athanasiou, Muhammed Kocabas, Nikos Kolotouros and Vassilis Choutas for the discussions. and Lea Muller, Amir Ahmad and Nitin Saini for proof reading the script and Joachim Tesch for help with game engines plug-ins. and Mason Laundry for the voice over.
For questions, please contact [email protected].
For commercial licensing (and all related questions for business applications), please contact [email protected].