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CIVR
2008
Springer
279views Image Analysis» more  CIVR 2008»
9 years 5 months ago
Semi-supervised learning of object categories from paired local features
This paper presents a semi-supervised learning (SSL) approach to find similarities of images using statistics of local matches. SSL algorithms are well known for leveraging a larg...
Wen Wu, Jie Yang
CVPR
2007
IEEE
10 years 5 months ago
Beyond Local Appearance: Category Recognition from Pairwise Interactions of Simple Features
We present a discriminative shape-based algorithm for object category localization and recognition. Our method learns object models in a weakly-supervised fashion, without requiri...
Marius Leordeanu, Martial Hebert, Rahul Sukthankar
CVPR
2006
IEEE
10 years 5 months ago
Unsupervised Learning of Categories from Sets of Partially Matching Image Features
We present a method to automatically learn object categories from unlabeled images. Each image is represented by an unordered set of local features, and all sets are embedded into...
Kristen Grauman, Trevor Darrell
CVPR
2007
IEEE
9 years 10 months ago
Local Ensemble Kernel Learning for Object Category Recognition
This paper describes a local ensemble kernel learning technique to recognize/classify objects from a large number of diverse categories. Due to the possibly large intraclass featu...
Yen-Yu Lin, Tyng-Luh Liu, Chiou-Shann Fuh
ICCV
2007
IEEE
10 years 5 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...
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