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» Structured Learning and Prediction in Computer Vision
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NIPS
1998
13 years 9 months ago
Learning from Dyadic Data
Dyadic data refers to a domain with two nite sets of objects in which observations are made for dyads, i.e., pairs with one element from either set. This type of data arises natur...
Thomas Hofmann, Jan Puzicha, Michael I. Jordan
CVPR
1999
IEEE
14 years 10 months ago
Shape from Recognition and Learning: Recovery of 3-D Face Shapes
In this paper, a novel framework for the recovery of 3D surfaces of faces from single images is developed. The underlying principle is shape from recognition, i.e. the idea that p...
Dibyendu Nandy, Jezekiel Ben-Arie
CVPR
2005
IEEE
14 years 10 months ago
A Sparse Object Category Model for Efficient Learning and Exhaustive Recognition
We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a semisupervised manner: the model is learnt from example ...
Robert Fergus, Pietro Perona, Andrew Zisserman
ICPR
2008
IEEE
14 years 9 months ago
Lexicon-based offline recognition of Amharic words in unconstrained handwritten text
This paper describes an offline handwriting recognition system for Amharic words based on lexicon. The system computes direction fields of scanned handwritten documents, from whic...
Yaregal Assabie, Josef Bigün
ICANN
2010
Springer
13 years 9 months ago
A Learned Saliency Predictor for Dynamic Natural Scenes
Abstract. We investigate the extent to which eye movements in natural dynamic scenes can be predicted with a simple model of bottom-up saliency, which learns on different visual re...
Eleonora Vig, Michael Dorr, Thomas Martinetz, Erha...