192 search results - page 29 / 39 » Learning Conditional Random Fields for Stereo |
FOIKS
2008
Springer
14 years 5 months ago
2008
Springer
Supervised learning deals with the inference of a distribution over an output or label space $\CY$ conditioned on points in an observation space $\CX$, given a training dataset $D$...
CVPR
2009
IEEE
15 years 3 months ago
2009
IEEE
A variety of flexible models have been proposed to detect
objects in challenging real world scenes. Motivated
by some of the most successful techniques, we propose a
hierarchica...
CVPR
2007
IEEE
14 years 10 months ago
2007
IEEE
We introduce novel discriminative learning algorithms for dynamical systems. Models such as Conditional Random Fields or Maximum Entropy Markov Models outperform the generative Hi...
ECCV
2006
Springer
14 years 10 months ago
2006
Springer
Bottom-up segmentation based only on low-level cues is a notoriously difficult problem. This difficulty has lead to recent top-down segmentation algorithms that are based on class-...
ECCV
2006
Springer
14 years 10 months ago
2006
Springer
Abstract. Bottom-up approaches, which rely mainly on continuity principles, are often insufficient to form accurate segments in natural images. In order to improve performance, rec...