Large-Scale Semantic 3D Reconstruction: an Adaptive Multi-Resolution Model for Multi-Class Volumetric Labeling

Maros Blaha; Christoph Vogel; Audrey Richard; Jan  Wegner; Konrad  Schindler; Thomas Pock

doi:10.1109/CVPR.2016.346

Large-Scale Semantic 3D Reconstruction: an Adaptive Multi-Resolution Model for Multi-Class Volumetric Labeling

Maros Blaha, Christoph Vogel, Audrey Richard, Jan Wegner, Konrad Schindler, Thomas Pock

Institute of Computer Graphics and Vision (7100)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Original language	English
Title of host publication	Computer Vision and Pattern Recognition
Publisher	IEEE Computer Society
Pages	3176-3184
Number of pages	9
ISBN (Electronic)	978-1-4673-8851-1
DOIs	https://doi.org/10.1109/CVPR.2016.346
Publication status	Published - 2016
Event	IEEE Conference on Computer Vision and Pattern Recognition, 2016: 2018 IEEE Conference on Computer Vision and Pattern Recognition - Salt Lake City, United States Duration: 18 Jun 2018 → 22 Jun 2018

Conference

Conference	IEEE Conference on Computer Vision and Pattern Recognition, 2016
Country	United States
City	Salt Lake City
Period	18/06/18 → 22/06/18

Access to Document

10.1109/CVPR.2016.346

LargeScale3DSFinal published version, 3.57 MB

Supplementary Material

Cite this

Large-Scale Semantic 3D Reconstruction: an Adaptive Multi-Resolution Model for Multi-Class Volumetric Labeling. / Blaha, Maros; Vogel, Christoph; Richard, Audrey; Wegner, Jan ; Schindler, Konrad ; Pock, Thomas.

Computer Vision and Pattern Recognition. IEEE Computer Society, 2016. p. 3176-3184.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Blaha, M, Vogel, C, Richard, A, Wegner, J, Schindler, K & Pock, T 2016, Large-Scale Semantic 3D Reconstruction: an Adaptive Multi-Resolution Model for Multi-Class Volumetric Labeling. in Computer Vision and Pattern Recognition. IEEE Computer Society, pp. 3176-3184, IEEE Conference on Computer Vision and Pattern Recognition, 2016, Salt Lake City, United States, 18/06/18. https://doi.org/10.1109/CVPR.2016.346

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