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  STD2P: RGBD Semantic Segmentation Using Spatio-Temporal Data-Driven Pooling

He, Y., Chiu, W.-C., Keuper, M., & Fritz, M. (2017). STD2P: RGBD Semantic Segmentation Using Spatio-Temporal Data-Driven Pooling. In 30th IEEE Conference on Computer Vision and Pattern Recognition (pp. 7158-7167). Los Alamitos, CA: IEEE Computer Society. doi:10.1109/CVPR.2017.757.

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Genre: Conference Paper
Latex : {STD2P}: {RGBD} Semantic Segmentation Using Spatio-Temporal Data-Driven Pooling

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 Creators:
He, Yang1, Author           
Chiu, Wei-Chen1, Author           
Keuper, Margret1, Author           
Fritz, Mario1, Author           
Affiliations:
1Computer Vision and Multimodal Computing, MPI for Informatics, Max Planck Society, ou_1116547              

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Language(s): eng - English
 Dates: 201720172017
 Publication Status: Issued
 Pages: 20 p.
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: yang_cvpr17
DOI: 10.1109/CVPR.2017.757
 Degree: -

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Title: 30th IEEE Conference on Computer Vision and Pattern Recognition
Place of Event: Honolulu, HI, USA
Start-/End Date: 2017-07-22 - 2017-07-25

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Title: 30th IEEE Conference on Computer Vision and Pattern Recognition
  Abbreviation : CVPR 2017
Source Genre: Proceedings
 Creator(s):
Affiliations:
Publ. Info: Los Alamitos, CA : IEEE Computer Society
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 7158 - 7167 Identifier: ISBN: 978-1-5386-0458-8