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» Multiscale Conditional Random Fields for Image Labeling
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EMMCVPR
2007
Springer
14 years 2 months ago
A New Bayesian Method for Range Image Segmentation
: We presented and evaluated a new Bayesian method for range image segmentation. The method proceeds in to stages. First, an initial segmentation was produced by a randomized regio...
Smaine Mazouzi, Mohamed Batouche
NIPS
2004
13 years 10 months ago
Contextual Models for Object Detection Using Boosted Random Fields
We seek to both detect and segment objects in images. To exploit both local image data as well as contextual information, we introduce Boosted Random Fields (BRFs), which use boos...
Antonio Torralba, Kevin P. Murphy, William T. Free...
CVPR
2010
IEEE
14 years 2 months ago
Towards Semantic Embedding in Visual Vocabulary
Visual vocabulary serves as a fundamental component in many computer vision tasks, such as object recognition, visual search, and scene modeling. While state-of-the-art approaches...
R.-R. Ji, Hongxun Yao, Xiaoshuai Sun
CVPR
2012
IEEE
11 years 11 months ago
Joint 2D-3D temporally consistent semantic segmentation of street scenes
In this paper we propose a novel Conditional Random Field (CRF) formulation for the semantic scene labeling problem which is able to enforce temporal consistency between consecuti...
Georgios Floros, Bastian Leibe
IJCV
2012
11 years 11 months ago
Harmony Potentials - Fusing Global and Local Scale for Semantic Image Segmentation
The Hierarchical Conditional Random Field (HCRF) model have been successfully applied to a number of image labeling problems, including image segmentation. However, existing HCRF m...
Xavier Boix, Josep M. Gonfaus, Joost van de Weijer...