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96
Voted
CVPR
2011
IEEE
14 years 5 months ago
Learning the Easy Things First: Self-Paced Visual Category Discovery
Objects vary in their visual complexity, yet existing discovery methods perform “batch” clustering, paying equal attention to all instances simultaneously—regardless of the ...
Yong Jae Lee, Kristen Grauman
ICCV
2011
IEEE
13 years 9 months ago
Tabula Rasa: Model Transfer for Object Category Detection
Our objective is transfer training of a discriminatively trained object category detector, in order to reduce the number of training images required. To this end we propose three ...
Yusuf Aytar, Andrew Zisserman
COLT
2005
Springer
14 years 11 months ago
Loss Bounds for Online Category Ranking
Category ranking is the task of ordering labels with respect to their relevance to an input instance. In this paper we describe and analyze several algorithms for online category r...
Koby Crammer, Yoram Singer
67
Voted
PAMI
2008
170views more  PAMI 2008»
14 years 9 months ago
Unsupervised Category Modeling, Recognition, and Segmentation in Images
Suppose a set of arbitrary (unlabeled) images contains frequent occurrences of 2D objects from an unknown category. This paper is aimed at simultaneously solving the following rel...
Sinisa Todorovic, Narendra Ahuja
66
Voted
ICCV
2009
IEEE
1019views Computer Vision» more  ICCV 2009»
16 years 2 months ago
Similarity Functions for Categorization: from Monolithic to Category Specific
Similarity metrics that are learned from labeled training data can be advantageous in terms of performance and/or efficiency. These learned metrics can then be used in conjuncti...
Boris Babenko, Steve Branson, Serge Belongie