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CVPR
2008
IEEE
14 years 7 months ago
A discriminatively trained, multiscale, deformable part model
This paper describes a discriminatively trained, multiscale, deformable part model for object detection. Our system achieves a two-fold improvement in average precision over the b...
Pedro F. Felzenszwalb, David A. McAllester, Deva R...
CVPR
2005
IEEE
14 years 7 months ago
Spatial Priors for Part-Based Recognition Using Statistical Models
We present a class of statistical models for part-based object recognition that are explicitly parameterized according to the degree of spatial structure they can represent. These...
David J. Crandall, Pedro F. Felzenszwalb, Daniel P...
ICASSP
2011
IEEE
12 years 9 months ago
Discriminative Training for direct minimization of deletion, insertion and substitution errors
In this paper, we follow the minimum error principle for acoustic modeling and formulate error objectives in insertion, deletion, and substitution separately for minimization duri...
Sunghwan Shin, Ho-Young Jung, Biing-Hwang Juang
CVPR
2005
IEEE
14 years 7 months ago
Generative versus Discriminative Methods for Object Recognition
Many approaches to object recognition are founded on probability theory, and can be broadly characterized as either generative or discriminative according to whether or not the di...
Ilkay Ulusoy, Christopher M. Bishop
ICCV
2011
IEEE
12 years 5 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