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  Self-Supervised Multi-level Face Model Learning for Monocular Reconstruction at Over 250 Hz

Tewari, A., Zollhöfer, M., Garrido, P., Bernard, F., Kim, H., Pérez, P., et al. (2018). Self-Supervised Multi-level Face Model Learning for Monocular Reconstruction at Over 250 Hz. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 2549-2559). Piscataway, NJ: IEEE. doi:10.1109/CVPR.2018.00270.

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Genre: Conference Paper
Latex : Self-Supervised Multi-level Face Model Learning for Monocular Reconstruction at Over 250 {Hz}

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 Creators:
Tewari, Ayush1, Author           
Zollhöfer, Michael1, Author           
Garrido, Pablo1, Author           
Bernard, Florian1, Author           
Kim, Hyeongwoo1, 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: 20182018
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: Teware_CVPR2018
DOI: 10.1109/CVPR.2018.00270
 Degree: -

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Title: 31st IEEE Conference on Computer Vision and Pattern Recognition
Place of Event: Salt Lake City, UT, USA
Start-/End Date: 2018-06-18 - 2018-06-22

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Title: IEEE/CVF Conference on Computer Vision and Pattern Recognition
  Abbreviation : CVPR 2018
  Subtitle : Proceedings
Source Genre: Proceedings
 Creator(s):
Affiliations:
Publ. Info: Piscataway, NJ : IEEE
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 2549 - 2559 Identifier: ISBN: 978-1-5386-6420-9