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International Journal of Computer Vision

Erschienen in:

01.04.2015

Labeling Complete Surfaces in Scene Understanding

verfasst von: Ruiqi Guo, Derek Hoiem

Erschienen in: International Journal of Computer Vision | Ausgabe 2/2015

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Abstract

Scene understanding requires reasoning about both what we can see and what is occluded. We offer a simple and general approach to infer labels of occluded background regions. Our approach incorporates estimates of visible surrounding background, detected objects, and shape priors from transferred training regions. We demonstrate the ability to infer the labels of occluded background regions in three datasets: the outdoor StreetScenes dataset, IndoorScene dataset and SUN09 dataset, all using the same approach. Furthermore, the proposed approach is extended to 3D space to find layered support surfaces in RGB-Depth scenes. Our experiments and analysis show that our method outperforms competent baselines.

Vorheriger Artikel Scene Parsing with Object Instance Inference Using Regions and Per-exemplar Detectors

Nächster Artikel Towards Scene Understanding with Detailed 3D Object Representations

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Titel: Labeling Complete Surfaces in Scene Understanding
verfasst von: Ruiqi Guo
Derek Hoiem
Publikationsdatum: 01.04.2015
Verlag: Springer US
Erschienen in: International Journal of Computer Vision / Ausgabe 2/2015
Print ISSN: 0920-5691
Elektronische ISSN: 1573-1405
DOI: https://doi.org/10.1007/s11263-014-0776-7

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