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» Learning Flexible Features for Conditional Random Fields
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CVPR
2006
IEEE
15 years 11 months ago
Training Deformable Models for Localization
We present a new method for training deformable models. Assume that we have training images where part locations have been labeled. Typically, one fits a model by maximizing the l...
Deva Ramanan, Cristian Sminchisescu
CVPR
2008
IEEE
15 years 11 months ago
Object categorization using co-occurrence, location and appearance
In this work we introduce a novel approach to object categorization that incorporates two types of context ? cooccurrence and relative location ? with local appearancebased featur...
Carolina Galleguillos, Andrew Rabinovich, Serge Be...
AAMAS
2010
Springer
14 years 9 months ago
A probabilistic multimodal approach for predicting listener backchannels
During face-to-face interactions, listeners use backchannel feedback such as head nods as a signal to the speaker that the communication is working and that they should continue sp...
Louis-Philippe Morency, Iwan de Kok, Jonathan Grat...
CVPR
2008
IEEE
15 years 11 months ago
Learning class-specific affinities for image labelling
Spectral clustering and eigenvector-based methods have become increasingly popular in segmentation and recognition. Although the choice of the pairwise similarity metric (or affin...
Dhruv Batra, Rahul Sukthankar, Tsuhan Chen
KDD
2005
ACM
153views Data Mining» more  KDD 2005»
15 years 10 months ago
Improving discriminative sequential learning with rare--but--important associations
Discriminative sequential learning models like Conditional Random Fields (CRFs) have achieved significant success in several areas such as natural language processing, information...
Xuan Hieu Phan, Minh Le Nguyen, Tu Bao Ho, Susumu ...