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Cited by 662

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Geometric context from a single image

Open access
Hoiem, D., Efros, A.A., Hebert, M.·2005·Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1

Abstract

Many computer vision algorithms limit their performance by ignoring the underlying 3D geometric structure in the image. We show that we can estimate the coarse geometric properties of a scene by learning appearance-based models of geometric classes, even in cluttered natural scenes. Geometric classes describe the 3D orientation of an image region with respect to the camera. We provide a multiple-hypothesis framework for robustly estimating scene structure from a single image and obtaining confidences for each geometric label. These confidences can then be used to improve the performance of many other applications. We provide a thorough quantitative evaluation of our algorithm on a set of outdoor images and demonstrate its usefulness in two applications: object detection and automatic single-view reconstruction.

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Crossref · 10.1109/iccv.2005.107

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Metadata

Authors
Hoiem, D., Efros, A. A., & Hebert, M.
Venue
Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1
Publisher
IEEE
Published
2005
Pages
654-661 Vol. 1
OpenAlex
W2155871590
Cited by
662
References
3
FWCI
18.24
Type
conference paper
Language
en
Open access
green

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