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» Learning Models for Object Recognition
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101
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ICASSP
2011
IEEE
14 years 1 months ago
Learning a discriminative visual codebook using homonym scheme
This paper studies a method for learning a discriminative visual codebook for various computer vision tasks such as image categorization and object recognition. The performance of...
SeungRyul Baek, Chang D. Yoo, Sungrack Yun
ICPR
2006
IEEE
15 years 11 months ago
A Semi-supervised SVM for Manifold Learning
Many classification tasks benefit from integrating manifold learning and semi-supervised learning. By formulating the learning task in a semi-supervised manner, we propose a novel...
Zhili Wu, Chun-hung Li, Ji Zhu, Jian Huang
TOG
2012
245views Communications» more  TOG 2012»
13 years 20 days ago
How do humans sketch objects?
Humans have used sketching to depict our visual world since prehistoric times. Even today, sketching is possibly the only rendering technique readily available to all humans. This...
Mathias Eitz, James Hays, Marc Alexa
82
Voted
CVPR
2003
IEEE
16 years 7 days ago
Learning Object Intrinsic Structure for Robust Visual Tracking
In this paper, a novel method to learn the intrinsic object structure for robust visual tracking is proposed. The basic assumption is that the parameterized object state lies on a...
Qiang Wang, Guangyou Xu, Haizhou Ai
92
Voted
AMFG
2005
IEEE
203views Biometrics» more  AMFG 2005»
15 years 3 months ago
Learning to Fuse 3D+2D Based Face Recognition at Both Feature and Decision Levels
2D intensity images and 3D shape models are both useful for face recognition, but in different ways. While algorithms have long been developed using 2D or 3D data, recently has see...
Stan Z. Li, ChunShui Zhao, Meng Ao, Zhen Lei