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» Multiscale Conditional Random Fields for Image Labeling
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CVPR
2008
IEEE
14 years 10 months ago
Combining appearance models and Markov Random Fields for category level object segmentation
Object models based on bag-of-words representations can achieve state-of-the-art performance for image classification and object localization tasks. However, as they consider obje...
Diane Larlus, Frédéric Jurie
AAAI
2006
13 years 10 months ago
Multi-Conditional Learning: Generative/Discriminative Training for Clustering and Classification
This paper presents multi-conditional learning (MCL), a training criterion based on a product of multiple conditional likelihoods. When combining the traditional conditional proba...
Andrew McCallum, Chris Pal, Gregory Druck, Xuerui ...
CVPR
2006
IEEE
14 years 10 months ago
AdaBoost.MRF: Boosted Markov Random Forests and Application to Multilevel Activity Recognition
Activity recognition is an important issue in building intelligent monitoring systems. We address the recognition of multilevel activities in this paper via a conditional Markov r...
Tran The Truyen, Dinh Q. Phung, Svetha Venkatesh, ...
DAGM
2011
Springer
12 years 8 months ago
Putting MAP Back on the Map
Conditional Random Fields (CRFs) are popular models in computer vision for solving labeling problems such as image denoising. This paper tackles the rarely addressed but important ...
Patrick Pletscher, Sebastian Nowozin, Pushmeet Koh...
ECCV
2008
Springer
14 years 10 months ago
Saliency Based Opportunistic Search for Object Part Extraction and Labeling
We study the task of object part extraction and labeling, which seeks to understand objects beyond simply identifiying their bounding boxes. We start from bottom-up segmentation of...
Yang Wu, Qihui Zhu, Jianbo Shi, Nanning Zheng