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  Adaptive Surface Normal Constraint for Depth Estimation

Long, X., Lin, C., Liu, L., Li, W., Theobalt, C., Yang, R., et al. (2021). Adaptive Surface Normal Constraint for Depth Estimation. In ICCV 2021 (pp. 12829-12838). Piscataway, NJ: IEEE. doi:10.1109/ICCV48922.2021.01261.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0009-5332-1 Version Permalink: https://hdl.handle.net/21.11116/0000-000E-3245-C
Genre: Conference Paper

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These ICCV 2021 papers are the Open Access versions, provided by the Computer Vision Foundation. Except for the watermark, they are identical to the accepted versions; the final published version of the proceedings is available on IEEE Xplore. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright.
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 Creators:
Long, Xiaoxiao1, Author
Lin, Cheng1, Author
Liu, Lingjie2, Author           
Li, Wei1, Author
Theobalt, Christian2, Author                 
Yang, Ruigang1, Author
Wang, Wenping1, Author
Affiliations:
1External Organizations, ou_persistent22              
2Visual Computing and Artificial Intelligence, MPI for Informatics, Max Planck Society, ou_3311330              

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Language(s): eng - English
 Dates: 2021-03-292021-07-122021
 Publication Status: Published online
 Pages: 10 p.
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: Long_ICCV21
DOI: 10.1109/ICCV48922.2021.01261
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Title: IEEE/CVF International Conference on Computer Vision
Place of Event: Virtual Event
Start-/End Date: 2021-10-11 - 2021-10-17

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Project name : 4DRepLy
Grant ID : 770784
Funding program : Horizon 2020 (H2020)
Funding organization : European Commission (EC)

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Title: ICCV 2021
  Abbreviation : ICCV 2021
  Subtitle : 2021 IEEE/CVF International Conference on Computer Vision ; Proceedings
Source Genre: Proceedings
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Publ. Info: Piscataway, NJ : IEEE
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 12829 - 12838 Identifier: ISBN: 978-1-6654-2812-5