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» A Conditional Random Field Model for Video Super-resolution
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ICCV
2011
IEEE
12 years 7 months ago
Decision Tree Fields
This paper introduces a new formulation for discrete image labeling tasks, the Decision Tree Field (DTF), that combines and generalizes random forests and conditional random fiel...
Sebastian Nowozin, Carsten Rother, Shai Bagon, Ban...
AAAI
2006
13 years 8 months ago
Multi-Conditional Learning: Generative/Discriminative Training for Clustering and Classification
This paper presents multi-conditional learning (MCL), a training criterion based on a product of multiple conditional likelihoods. When combining the traditional conditional proba...
Andrew McCallum, Chris Pal, Gregory Druck, Xuerui ...
ICMCS
2008
IEEE
211views Multimedia» more  ICMCS 2008»
14 years 1 months ago
A real-time video surveillance system with human occlusion handling using nonlinear regression
This paper presents a real-time single-camera surveillance system, aiming at detecting and partly analyzing a group of people. A set of moving persons is segmented using a combina...
Jungong Han, Minwei Feng, Peter H. N. de With
CVPR
2007
IEEE
14 years 9 months ago
Discriminative Learning of Dynamical Systems for Motion Tracking
We introduce novel discriminative learning algorithms for dynamical systems. Models such as Conditional Random Fields or Maximum Entropy Markov Models outperform the generative Hi...
Minyoung Kim, Vladimir Pavlovic
ACCV
2006
Springer
14 years 1 months ago
Markovian Framework for Foreground-Background-Shadow Separation of Real World Video Scenes
Abstract. In this paper we give a new model for foreground-background-shadow separation. Our method extracts the faithful silhouettes of foreground objects even if they have partly...
Csaba Benedek, Tamás Szirányi