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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. (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.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0000-6102-0 Version Permalink: https://hdl.handle.net/21.11116/0000-0000-6103-F
Genre: Conference Paper

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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: 2017-03-30201720172017
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: TewariICCV2017
DOI: 10.1109/ICCV.2017.401
 Degree: -

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Title: International Conference on Computer Vision
Place of Event: Venice, Italy
Start-/End Date: 2017-10-22 - 2017-10-29

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Title: IEEE International Conference on Computer Vision
  Abbreviation : ICCV 2017
  Subtitle : Proceedings
Source Genre: Proceedings
 Creator(s):
Affiliations:
Publ. Info: Piscataway, NJ : IEEE
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 3735 - 3744 Identifier: ISBN: 978-1-5386-1032-9