POOF: Part-Based One-vs.-One Features for Fine-Grained Categorization, Face Verification, and Attribute Estimation

From a set of images in a particular domain, labeled with part locations and class, we present a method to automatically learn a large and diverse set of highly discriminative intermediate features that we call Part-based One-vs.-One Features (POOFs). Each of these features specializes in discrimina...

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Vydané v:	2013 IEEE Conference on Computer Vision and Pattern Recognition s. 955 - 962
Hlavní autori:	Berg, Thomas, Belhumeur, Peter N.
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.06.2013
Predmet:	Accuracy attributes Birds Face face verification Feature extraction fine-grained visual categorization Histograms Image color analysis part-based recognition Training
ISSN:	1063-6919, 1063-6919
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