Abstract

Westudythechallengingproblemoflocalizingandclassifying category-specific object contours in real world images. For this purpose, we present a simple yet effective methodforcombininggenericobjectdetectorswithbottomup contours to identify object contours. We also provide a principledwayofcombininginformationfromdifferentpart detectors and across categories. Inorder tostudy theproblem 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 theimages from theVOC2011 PASCAL challenge [7].

Keywords

Pascal (unit)Computer scienceObject (grammar)Object detectionDetectorArtificial intelligenceComputer visionInverseInverse problemPattern recognition (psychology)MathematicsGeometry

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Year
2011
Type
article
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1695
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Bharath Hariharan, Pablo Arbeláez, Lubomir Bourdev et al. (2011). Semantic contours from inverse detectors. . https://doi.org/10.1109/iccv.2011.6126343

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DOI
10.1109/iccv.2011.6126343