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» Multiscale Conditional Random Fields for Image Labeling
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CVPR
2004
IEEE
14 years 6 months ago
Multiscale Conditional Random Fields for Image Labeling
We propose an approach to include contextual features for labeling images, in which each pixel is assigned to one of a finite set of labels. The features are incorporated into a p...
Miguel Á. Carreira-Perpiñán, ...
CVPR
2003
IEEE
14 years 6 months ago
Man-Made Structure Detection in Natural Images using a Causal Multiscale Random Field
This paper presents a generative model based approach to man-made structure detection in 2D natural images. The proposed approach uses a causal multiscale random field suggested i...
Sanjiv Kumar, Martial Hebert
ICASSP
2011
IEEE
12 years 8 months ago
Superpixel-based object class segmentation using conditional random fields
Object class segmentation (OCS) is a key issue in semantic scene labeling and understanding. Its general principle consists of naming object entities into scenes according to thei...
Xi Li, Hichem Sahbi
CVPR
2011
IEEE
12 years 8 months ago
A Hierarchical Conditional Random Field Model for Labeling and Segmenting Images of Street Scenes
Simultaneously segmenting and labeling images is a fundamental problem in Computer Vision. In this paper, we introduce a hierarchical CRF model to deal with the problem of labelin...
Qixing Huang, Mei Han, Bo Wu, Sergey Ioffe
ICDAR
2009
IEEE
13 years 2 months ago
Unconstrained Handwritten Document Layout Extraction Using 2D Conditional Random Fields
The paper describes a new approach using a Conditional Random Fields (CRFs) to extract physical and logical layouts in unconstrained handwritten letters such as those sent by indi...
Florent Montreuil, Emmanuele Grosicki, Laurent Heu...