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ICPR
2006
IEEE
15 years 2 days ago
Image Renaissance Using Discrete Optimization
In this paper we propose a novel technique to image completion that addresses image renaissance through a graph-based matching process. To this end, a number of candidate seeds wi...
Cédric Allène, Nikos Paragios
CVPR
2009
IEEE
15 years 6 months ago
Half-integrality based algorithms for Cosegmentation of Images
We study the cosegmentation problem where the objective is to segment the same object (i.e., region) from a pair of images. The segmentation for each image can be cast using a p...
Chuck R. Dyer, Lopamudra Mukherjee, Vikas Singh
CVPR
2010
IEEE
14 years 6 months ago
Efficient Piecewise Learning for Conditional Random Fields
Conditional Random Field models have proved effective for several low-level computer vision problems. Inference in these models involves solving a combinatorial optimization probl...
Karteek Alahari, Phil Torr
ICCV
2011
IEEE
12 years 11 months ago
Perturb-and-MAP Random Fields: Using Discrete Optimization\\to Learn and Sample from Energy Models
We propose a novel way to induce a random field from an energy function on discrete labels. It amounts to locally injecting noise to the energy potentials, followed by finding t...
George Papandreou, Alan L. Yuille
CVPR
2004
IEEE
15 years 1 months ago
Multiscale Conditional Random Fields for Image Labeling
We propose an approach to include contextual features for labeling images, in which each pixel is assigned to one of a finite set of labels. The features are incorporated into a p...
Miguel Á. Carreira-Perpiñán, ...