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» Learning Generative Models via Discriminative Approaches
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ICCV
2003
IEEE
15 years 1 months ago
Ranking Prior Likelihood Distributions for Bayesian Shape Localization Framework
In this paper, we formulate the shape localization problem in the Bayesian framework. In the learning stage, we propose the Constrained RankBoost approach to model the likelihood ...
Shuicheng Yan, Mingjing Li, HongJiang Zhang, QianS...
ICCV
2011
IEEE
12 years 11 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
CVPR
2009
IEEE
1002views Computer Vision» more  CVPR 2009»
15 years 6 months ago
Classifier Grids for Robust Adaptive Object Detection
In this paper we present an adaptive but robust object detector for static cameras by introducing classifier grids. Instead of using a sliding window for object detection we pro...
Peter M. Roth, Sabine Sternig, Helmut Grabner, Hor...
MIR
2006
ACM
141views Multimedia» more  MIR 2006»
14 years 5 months ago
Mining temporal patterns of movement for video content classification
Scalable approaches to video content classification are limited by an inability to automatically generate representations of events ode abstract temporal structure. This paper pre...
Michael Fleischman, Philip DeCamp, Deb Roy
CVPR
2009
IEEE
15 years 6 months ago
Learning Optimized MAP Estimates in Continuously-Valued MRF Models
We present a new approach for the discriminative training of continuous-valued Markov Random Field (MRF) model parameters. In our approach we train the MRF model by optimizing t...
Kegan G. G. Samuel, Marshall F. Tappen