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» PAMPAS: Real-Valued Graphical Models for Computer Vision
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JMLR
2006
125views more  JMLR 2006»
14 years 10 months ago
Linear Programming Relaxations and Belief Propagation - An Empirical Study
The problem of finding the most probable (MAP) configuration in graphical models comes up in a wide range of applications. In a general graphical model this problem is NP hard, bu...
Chen Yanover, Talya Meltzer, Yair Weiss
ECCV
2010
Springer
15 years 2 months ago
The Semi-Explicit Shape Model for Multi-object Detection and Classification
We propose a model for classification and detection of object classes where the number of classes may be large and where multiple instances of object classes may be present in an i...
CVPR
2007
IEEE
16 years 14 hour ago
On-line Simultaneous Learning and Tracking of Visual Feature Graphs
Model learning and tracking are two important topics in computer vision. While there are many applications where one of them is used to support the other, there are currently only...
Arnaud Declercq, Justus H. Piater
CVPR
2003
IEEE
16 years 14 hour ago
Nonparametric Belief Propagation
In many applications of graphical models arising in computer vision, the hidden variables of interest are most naturally specified by continuous, non-Gaussian distributions. There...
Erik B. Sudderth, Alexander T. Ihler, William T. F...
GRAPHITE
2007
ACM
15 years 1 months ago
A shape hierarchy for 3D modelling from video
This paper describes an interactive method for generating a model of a scene from image data. The method uses the camera parameters and point cloud typically generated by structur...
Anton van den Hengel, Anthony R. Dick, Thorsten Th...