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» Decomposition of range images using markov random fields
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NIPS
2003
13 years 9 months ago
Discriminative Fields for Modeling Spatial Dependencies in Natural Images
In this paper we present Discriminative Random Fields (DRF), a discriminative framework for the classification of natural image regions by incorporating neighborhood spatial depe...
Sanjiv Kumar, Martial Hebert
CVPR
2008
IEEE
14 years 9 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
ICPR
2004
IEEE
14 years 8 months ago
Photometric Stereo Under Blurred Observations
In this paper we address the problem of simultaneous estimation of structure and restoration of images from blurred photometric measurements. Given the blurred observations of a s...
Manjunath V. Joshi, Subhasis Chaudhuri
CVPR
2007
IEEE
14 years 9 months ago
Learning Gaussian Conditional Random Fields for Low-Level Vision
Markov Random Field (MRF) models are a popular tool for vision and image processing. Gaussian MRF models are particularly convenient to work with because they can be implemented u...
Marshall F. Tappen, Ce Liu, Edward H. Adelson, Wil...
ICRA
2009
IEEE
158views Robotics» more  ICRA 2009»
13 years 5 months ago
MMM-classification of 3D range data
This paper presents a method for accurately segmenting and classifying 3D range data into particular object classes. Object classification of input images is necessary for applicat...
Anuraag Agrawal, Atsushi Nakazawa, Haruo Takemura