RingNet: Learning to Regress 3D Face Shape and Expression from an Image without 3D Supervision
2019-05-10
Code: We provide the inference code of RingNet. Please check the repository which is self explanatory. NoW Benchmark Dataset and Challenge: Please check the external link to download the data and participate in the challenge.
| Author(s): | Soubhik Sanyal and Timo Bolkart and Haiwen Feng and Michael Black |
| Department(s): |
Perceiving Systems |
| Research Projects(s): |
Faces and Expressions |
| Publication(s): |
Learning to Regress 3D Face Shape and Expression from an Image without 3D Supervision
|
| Authors: | Soubhik Sanyal and Timo Bolkart and Haiwen Feng and Michael Black |
| Maintainers: | Soubhik Sanyal and Timo Bolkart |
| Release Date: | 2019-05-10 |
| License: | The MIT License (MIT) |
| Copyright: | Max-Planck-Gesellschaft zur Förderung der Wissenschaften e.V. |
| Repository: | https://github.com/soubhiksanyal/RingNet |
| External Link: | https://ringnet.is.tue.mpg.de |
