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» Unsupervised Object Discovery: A Comparison
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CVPR
2008
IEEE
14 years 11 months ago
Decomposition, discovery and detection of visual categories using topic models
We present a novel method for the discovery and detection of visual object categories based on decompositions using topic models. The approach is capable of learning a compact and...
Mario Fritz, Bernt Schiele
CVPR
2000
IEEE
14 years 11 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
BMVC
2010
13 years 7 months ago
Image Topic Discovery with Saliency Detection
This work proposes a biologically inspired approach to integrate latent topic model with saliency detection. Firstly, a saliency detection algorithm is presented to discriminate s...
Zhidong Li, Yang Wang, Jing Chen, Jie Xu, John Lai...
INFOSCALE
2006
ACM
14 years 3 months ago
Analysis and comparison of P2P search methods
The popularity and bandwidth consumption attributed to current Peer-to-Peer file-sharing applications makes the operation of these distributed systems very important for the Inte...
Dimitrios Tsoumakos, Nick Roussopoulos
CVPR
2006
IEEE
14 years 11 months ago
Escaping local minima through hierarchical model selection: Automatic object discovery, segmentation, and tracking in video
Recently, the generative modeling approach to video segmentation has been gaining popularity in the computer vision community. For example, the flexible sprites framework has been...
Nebojsa Jojic, John M. Winn, Larry Zitnick