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» The Dark Side of Object Learning: Learning Objects
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ICCV
2011
IEEE
12 years 9 months ago
Domain Adaptation for Object Recognition: An Unsupervised Approach
Adapting the classifier trained on a source domain to recognize instances from a new target domain is an important problem that is receiving recent attention. In this paper, we p...
Raghuraman Gopalan, Ruonan Li, Rama Chellappa
CVPR
2001
IEEE
14 years 11 months ago
Bayesian Color Constancy for Outdoor Object Recognition
Outdoor scene classification is challenging due to irregular geometry, uncontrolled illumination, and noisy reflectance distributions. This paper discusses a Bayesian approach to ...
Yanghai Tsin, Robert T. Collins, Visvanathan Rames...
CVPR
2008
IEEE
14 years 11 months ago
Similarity-based cross-layered hierarchical representation for object categorization
This paper proposes a new concept in hierarchical representations that exploits features of different granularity and specificity coming from all layers of the hierarchy. The conc...
Sanja Fidler, Marko Boben, Ales Leonardis
CVPR
2008
IEEE
14 years 11 months ago
Unsupervised modeling of object categories using link analysis techniques
We propose an approach for learning visual models of object categories in an unsupervised manner in which we first build a large-scale complex network which captures the interacti...
Gunhee Kim, Christos Faloutsos, Martial Hebert
ICCV
2005
IEEE
14 years 11 months ago
Feature Hierarchies for Object Classification
The paper describes a method for automatically extracting informative feature hierarchies for object classification, and shows the advantage of the features constructed hierarchic...
Boris Epshtein, Shimon Ullman