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

Tewari, A., Zollhöfer, M., Kim, H., Garrido, P., Bernard, F., Pérez, P., et al. (in press). MoFA: Model-based Deep Convolutional Face Autoencoder for Unsupervised Monocular Reconstruction. In International Conference on Computer Vision.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-002D-C2F7-4 Version Permalink: https://hdl.handle.net/11858/00-001M-0000-002D-C2F9-F
Genre: Conference Paper
Latex : {MoFA}: Model-based Deep Convolutional Face Autoencoder for Unsupervised Monocular Reconstruction

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 Creators:
Tewari, Ayush1, Author           
Zollhöfer, Michael1, Author           
Kim, Hyeongwoo1, Author           
Garrido, Pablo1, Author           
Bernard, Florian2, Author
Pérez, Patrick2, Author
Theobalt, Christian1, Author           
Affiliations:
1Computer Graphics, MPI for Informatics, Max Planck Society, ou_40047              
2External Organizations, ou_persistent22              

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Language(s): eng - English
 Dates: 2017
 Publication Status: Accepted / In Press
 Pages: -
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 Rev. Type: -
 Identifiers: BibTex Citekey: tewari17MoFA
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Title: International Conference on Computer Vision
Place of Event: Venice, Italy
Start-/End Date: 2017-10-22 - 2017-10-28

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Title: International Conference on Computer Vision
  Abbreviation : ICCV 2017
Source Genre: Proceedings
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