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» Surface Reconstruction using Learned Shape Models
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CVPR
2007
IEEE
14 years 11 months ago
Hybrid learning of large jigsaws
A jigsaw is a recently proposed generative model that describes an image as a composition of non-overlapping patches of varying shape, extracted from a latent image. By learning t...
Julia A. Lasserre, Anitha Kannan, John M. Winn
JMM2
2008
124views more  JMM2 2008»
13 years 8 months ago
Integrated Feature Selection and Clustering for Taxonomic Problems within Fish Species Complexes
As computer and database technologies advance rapidly, biologists all over the world can share biologically meaningful data from images of specimens and use the data to classify th...
Huimin Chen, Henry L. Bart Jr., Shuqing Huang
ECCV
2010
Springer
13 years 6 months ago
Non-local Characterization of Scenery Images: Statistics, 3D Reasoning, and a Generative Model
Abstract. This work focuses on characterizing scenery images. We semantically divide the objects in natural landscape scenes into background and foreground and show that the shapes...
Tamar Avraham, Michael Lindenbaum
PAMI
2012
11 years 11 months ago
Unsupervised Learning of Categorical Segments in Image Collections
Which one comes first: segmentation or recognition? We propose a unified framework for carrying out the two simultaneously and without supervision. The framework combines a fle...
Marco Andreetto, Lihi Zelnik-Manor, Pietro Perona
ECCV
2000
Springer
14 years 10 months ago
A Physically-Based Statistical Deformable Model for Brain Image Analysis
A probabilistic deformable model for the representation of brain structures is described. The statistically learned deformable model represents the relative location of head (skull...
Christophoros Nikou, Fabrice Heitz, Jean-Paul Arms...