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» A Dynamic Conditional Random Field Model for Joint Labeling ...
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ICML
2007
IEEE
14 years 8 months ago
Conditional random fields for multi-agent reinforcement learning
Conditional random fields (CRFs) are graphical models for modeling the probability of labels given the observations. They have traditionally been trained with using a set of obser...
Xinhua Zhang, Douglas Aberdeen, S. V. N. Vishwanat...
BMVC
2010
13 years 5 months ago
Joint Optimisation for Object Class Segmentation and Dense Stereo Reconstruction
The problems of dense stereo reconstruction and object class segmentation can both be formulated as Conditional Random Field based labelling problems, in which every pixel in the ...
Lubor Ladicky, Paul Sturgess, Christopher Russell,...
NIPS
2004
13 years 8 months ago
Conditional Random Fields for Object Recognition
We present a discriminative part-based approach for the recognition of object classes from unsegmented cluttered scenes. Objects are modeled as flexible constellations of parts co...
Ariadna Quattoni, Michael Collins, Trevor Darrell
CVPR
2005
IEEE
14 years 9 months ago
Bayesian Object Detection in Dynamic Scenes
Detecting moving objects using stationary cameras is an important precursor to many activity recognition, object recognition and tracking algorithms. In this paper, three innovati...
Yaser Sheikh, Mubarak Shah
AAAI
2008
13 years 9 months ago
Hidden Dynamic Probabilistic Models for Labeling Sequence Data
We propose a new discriminative framework, namely Hidden Dynamic Conditional Random Fields (HDCRFs), for building probabilistic models which can capture both internal and external...
Xiaofeng Yu, Wai Lam