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» Learning GMRF Structures for Spatial Priors
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ICCV
2005
IEEE
13 years 11 months ago
On the Spatial Statistics of Optical Flow
We develop a method for learning the spatial statistics of optical flow fields from a novel training database. Training flow fields are constructed using range images of natur...
Stefan Roth, Michael J. Black
JCDL
2011
ACM
221views Education» more  JCDL 2011»
12 years 8 months ago
Integrating implicit structure visualization with authoring promotes ideation
We need to harness the growing wealth of information in digital libraries to support intellectual work involving creative and exploratory processes. Prior research on hypertext au...
Andrew M. Webb, Andruid Kerne
CVPR
2008
IEEE
14 years 7 months ago
Hybrid body representation for integrated pose recognition, localization and segmentation
We propose a hybrid body representation that represents each typical pose by both template-like view information and part-based structural information. Specifically, each body par...
Cheng Chen, Guoliang Fan
CVPR
2008
IEEE
13 years 11 months ago
Scene understanding with discriminative structured prediction
Spatial priors play crucial roles in many high-level vision tasks, e.g. scene understanding. Usually, learning spatial priors relies on training a structured output model. In this...
Jinhui Yuan, Jianmin Li, Bo Zhang
NIPS
2008
13 years 6 months ago
Learning Hybrid Models for Image Annotation with Partially Labeled Data
Extensive labeled data for image annotation systems, which learn to assign class labels to image regions, is difficult to obtain. We explore a hybrid model framework for utilizing...
Xuming He, Richard S. Zemel