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» Learning in Gaussian Markov random fields
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ECCV
2004
Springer
16 years 7 months ago
Interactive Image Segmentation Using an Adaptive GMMRF Model
The problem of interactive foreground/background segmentation in still images is of great practical importance in image editing. The state of the art in interactive segmentation is...
Andrew Blake, Carsten Rother, M. Brown, Patrick P&...
CVPR
2009
IEEE
17 years 15 days ago
Contextual Classification with Functional Max-Margin Markov Networks
We address the problem of label assignment in computer vision: given a novel 3-D or 2-D scene, we wish to assign a unique label to every site (voxel, pixel, superpixel, etc.). To...
Daniel Munoz, James A. Bagnell, Martial Hebert, Ni...
ICDAR
2011
IEEE
14 years 5 months ago
A Novel Italic Detection and Rectification Method for Chinese Advertising Images
—The italic detection and slant rectification is a key step of optical character recognition (OCR). In this paper, a novel method is proposed to detect and rectify italic charact...
Jie Liu, Heping Li, Shuwu Zhang, Wei Liang
EMMCVPR
2005
Springer
15 years 11 months ago
Exploiting Inference for Approximate Parameter Learning in Discriminative Fields: An Empirical Study
Abstract. Estimation of parameters of random field models from labeled training data is crucial for their good performance in many image analysis applications. In this paper, we p...
Sanjiv Kumar, Jonas August, Martial Hebert
CVPR
2008
IEEE
16 years 7 months ago
Consistent image analogies using semi-supervised learning
In this paper we study the following problem: given two source images A and A , and a target image B, can we learn to synthesize a new image B which relates to B in the same way t...
Li Cheng, S. V. N. Vishwanathan, Xinhua Zhang