English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Conference Paper

MoFA: Model-Based Deep Convolutional Face Autoencoder for Unsupervised Monocular Reconstruction

MPS-Authors
/persons/resource/persons206546

Tewari,  Ayush
Computer Graphics, MPI for Informatics, Max Planck Society;

/persons/resource/persons136490

Zollhöfer,  Michael
Computer Graphics, MPI for Informatics, Max Planck Society;

/persons/resource/persons127713

Kim,  Hyeongwoo
Computer Graphics, MPI for Informatics, Max Planck Society;

/persons/resource/persons127194

Garrido,  Pablo
Computer Graphics, MPI for Informatics, Max Planck Society;

/persons/resource/persons45610

Theobalt,  Christian
Computer Graphics, MPI for Informatics, Max Planck Society;

Locator
There are no locators available
Fulltext (public)
There are no public fulltexts available
Supplementary Material (public)
There is no public supplementary material available
Citation

Tewari, A., Zollhöfer, M., Kim, H., Garrido, P., Bernard, F., Pérez, P., et al. (2017). MoFA: Model-Based Deep Convolutional Face Autoencoder for Unsupervised Monocular Reconstruction. In IEEE International Conference on Computer Vision (pp. 3735-3744). Piscataway, NJ: IEEE. doi:10.1109/ICCV.2017.401.


Cite as: http://hdl.handle.net/21.11116/0000-0000-6102-0
Abstract
There is no abstract available