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DAGM
2006
Springer
13 years 8 months ago
Towards Unsupervised Discovery of Visual Categories
Recently, many approaches have been proposed for visual object category detection. They vary greatly in terms of how much supervision is needed. High performance object detection m...
Mario Fritz, Bernt Schiele
CVPR
2010
IEEE
13 years 8 months ago
Harvesting Large-Scale Weakly-Tagged Image Databases from the Web
To leverage large-scale weakly-tagged images for computer vision tasks (such as object detection and scene recognition), a novel cross-modal tag cleansing and junk image filtering...
Jianping Fan
ICCV
2003
IEEE
14 years 6 months ago
A Bayesian Approach to Unsupervised One-Shot Learning of Object Categories
Learning visual models of object categories notoriously requires thousands of training examples; this is due to the diversity and richness of object appearance which requires mode...
Fei-Fei Li 0002, Robert Fergus, Pietro Perona
CVPR
2000
IEEE
14 years 6 months ago
Towards Automatic Discovery of Object Categories
We propose a method to learn heterogeneous models of object classes for visual recognition. The training images contain a preponderance of clutter and learning is unsupervised. Ou...
Markus Weber, Max Welling, Pietro Perona
CVPR
2008
IEEE
13 years 6 months ago
Loose shape model for discriminative learning of object categories
We consider the problem of visual categorization with minimal supervision during training. We propose a partbased model that loosely captures structural information. We represent ...
Margarita Osadchy, Elran Morash