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SMPLify: 3D human pose and shape estimation from a single image

2016-10-08


Given a single image, extract the 3D SMPL pose and shape parameters. We provide a Python demo code needed to run SMPLify. We also provide results from the ECCV paper for comparison. For all the datasets we used (LSP, HumanEva-I, Human3.6M) we provide the detected joints and our results as SMPL model parameters and as a mesh (vertices and faces). The code package includes an example script showing how to load results. Please see the README in the code package and the FAQ.

Author(s): Bogo, Federica and Kanazawa, Angjoo and Lassner, Christoph and Gehler, Peter and Romero, Javier and Black, Michael J.
Department(s): Perceiving Systems
Authors: Bogo, Federica and Kanazawa, Angjoo and Lassner, Christoph and Gehler, Peter and Romero, Javier and Black, Michael J.
Release Date: 2016-10-08
Copyright: Max-Planck-Gesellschaft zur Förderung der Wissenschaften e.V.
External Link: http://smplify.is.tue.mpg.de/