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/ |
