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Data-Driven 3D Primitives for Single Image Understanding

David Fouhey, Abhinav Gupta and Martial Hebert
Conference Paper, Carnegie Mellon University, International Conference on Computer Vision, December, 2013

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Abstract

What primitives should we use to infer the rich 3D world behind an image? We argue that these primitives should be both visually discriminative and geometrically informative and we present a technique for discovering such primitives. We demonstrate the utility of our primitives by using them to infer 3D surface normals given a single image. Our technique substantially outperforms the state-of-the-art and shows improved cross-dataset performance.

BibTeX Reference
@conference{Fouhey-2013-7799,
title = {Data-Driven 3D Primitives for Single Image Understanding},
author = {David Fouhey and Abhinav Gupta and Martial Hebert},
booktitle = {International Conference on Computer Vision},
school = {Robotics Institute , Carnegie Mellon University},
month = {December},
year = {2013},
address = {Pittsburgh, PA},
}
2017-09-13T10:39:13+00:00