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» Multiscale Conditional Random Fields for Image Labeling
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CVPR
2007
IEEE
14 years 9 months ago
Learning to Detect A Salient Object
We study visual attention by detecting a salient object in an input image. We formulate salient object detection as an image segmentation problem, where we separate the salient obj...
Tie Liu, Jian Sun, Nanning Zheng, Xiaoou Tang, Heu...
PREMI
2009
Springer
14 years 2 months ago
Unsupervised Color Image Segmentation Using Compound Markov Random Field Model
Abstract. In this paper, we propose an unsupervised color image segmentation scheme using homotopy continuation method and Compound Markov Random Field (CMRF) model. The proposed s...
Sucheta Panda, P. K. Nanda
NIPS
2003
13 years 8 months ago
Discriminative Fields for Modeling Spatial Dependencies in Natural Images
In this paper we present Discriminative Random Fields (DRF), a discriminative framework for the classification of natural image regions by incorporating neighborhood spatial depe...
Sanjiv Kumar, Martial Hebert
ACL
2008
13 years 9 months ago
Generalized Expectation Criteria for Semi-Supervised Learning of Conditional Random Fields
This paper presents a semi-supervised training method for linear-chain conditional random fields that makes use of labeled features rather than labeled instances. This is accompli...
Gideon S. Mann, Andrew McCallum
CVPR
2008
IEEE
14 years 9 months ago
Latent topic random fields: Learning using a taxonomy of labels
An important problem in image labeling concerns learning with images labeled at varying levels of specificity. We propose an approach that can incorporate images with labels drawn...
Xuming He, Richard S. Zemel