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EMMCVPR
2007
Springer
14 years 5 months ago
Bayesian Inference for Layer Representation with Mixed Markov Random Field
Abstract. This paper presents a Bayesian inference algorithm for image layer representation [26], 2.1D sketch [6], with mixed Markov random field. 2.1D sketch is an very important...
Ru-Xin Gao, Tianfu Wu, Song Chun Zhu, Nong Sang
KDD
2010
ACM
274views Data Mining» more  KDD 2010»
14 years 2 months ago
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
Jun Zhu, Ni Lao, Eric P. Xing
ICASSP
2010
IEEE
13 years 9 months ago
Learning in Gaussian Markov random fields
This paper addresses the problem of state estimation in the case where the prior distribution of the states is not perfectly known but instead is parameterized by some unknown par...
Thomas J. Riedl, Andrew C. Singer, Jun Won Choi
CVPR
2008
IEEE
15 years 28 days 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
ICIP
2007
IEEE
15 years 18 days ago
Automatic Parametrisation for an Image Completion Method Based on Markov Random Fields
Recently, a new exemplar-based method for image completion, texture synthesis and image inpainting was proposed which uses a discrete global optimization strategy based on Markov ...
Huy Tho Ho, Roland Göcke