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ECCV
2010
Springer
9 years 3 months ago
Efficient object category recognition using classemes
We introduce a new descriptor for images which allows the construction of efficient and compact classifiers with good accuracy on object category recognition. The descriptor is the...
CLOR
2006
9 years 3 months ago
A Sparse Object Category Model for Efficient Learning and Complete Recognition
We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a weakly-supervised manner: the model is learnt from examp...
Robert Fergus, Pietro Perona, Andrew Zisserman
ICPR
2008
IEEE
9 years 6 months ago
Support Vector Data Description for image categorization from Internet images
Training a classi´Čüer for object category recognition using images on the Internet is an attractive approach due to its scalability. However, a big challenge in this approach is ...
Xiaodong Yu, Daniel DeMenthon, David S. Doermann
ICPR
2010
IEEE
9 years 6 months ago
On a Quest for Image Descriptors Based on Unsupervised Segmentation Maps
This paper investigates segmentation-based image descriptors for object category recognition. In contrast to commonly used interest points the proposed descriptors are extracted f...
Piotr Koniusz, Krystian Mikolajczyk
CVPR
2010
IEEE
9 years 8 months ago
Optimizing One-Shot Recognition with Micro-Set Learning
For object category recognition to scale beyond a small number of classes, it is important that algorithms be able to learn from a small amount of labeled data per additional clas...
Kevin Tang, Marshall Tappen, Rahul Sukthankar, Chr...
ICCV
2007
IEEE
10 years 2 months ago
Active Learning with Gaussian Processes for Object Categorization
Discriminative methods for visual object category recognition are typically non-probabilistic, predicting class labels but not directly providing an estimate of uncertainty. Gauss...
Ashish Kapoor, Kristen Grauman, Raquel Urtasun, Tr...
ICCV
2007
IEEE
10 years 2 months ago
An Empirical Study of Object Category Recognition: Sequential Testing with Generalized Samples
In this paper we present an empirical study of object category recognition using generalized samples and a set of sequential tests. We study 33 categories, each consisting of a sm...
Liang Lin, Shaowu Peng, Jake Porway, Song Chun Zhu...
CVPR
2005
IEEE
10 years 2 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
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