Semantic contours from inverse detectors

Authors:
Bharath Hariharan;Pablo Arbelaez;Lubomir Bourdev;Subhransu Maji;Jitendra Malik
Affiliations:
EECS, U.C. Berkeley, CA 94720, USA;EECS, U.C. Berkeley, CA 94720, USA;EECS, U.C. Berkeley, CA 94720, USA;EECS, U.C. Berkeley, CA 94720, USA;EECS, U.C. Berkeley, CA 94720, USA
Venue:
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
Year:
2011

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Abstract

We study the challenging problem of localizing and classifying category-specific object contours in real world images. For this purpose, we present a simple yet effective method for combining generic object detectors with bottom-up contours to identify object contours. We also provide a principled way of combining information from different part detectors and across categories. In order to study the problem and evaluate quantitatively our approach, we present a dataset of semantic exterior boundaries on more than 20, 000 object instances belonging to 20 categories, using the images from the VOC2011 PASCAL challenge [7].