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» Learning Models for Object Recognition
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CVPR
2010
IEEE
13 years 9 months ago
Attribute-centric recognition for cross-category generalization
We propose an approach to find and describe objects within broad domains. We introduce a new dataset that provides annotation for sharing models of appearance and correlation acr...
Ali Farhadi, Ian Endres, Derek Hoiem
CORR
2011
Springer
222views Education» more  CORR 2011»
13 years 22 days ago
Weakly Supervised Learning of Foreground-Background Segmentation using Masked RBMs
Abstract. We propose an extension of the Restricted Boltzmann Machine (RBM) that allows the joint shape and appearance of foreground objects in cluttered images to be modeled indep...
Nicolas Heess, Nicolas Le Roux, John M. Winn
ICIP
2007
IEEE
14 years 3 months ago
Group Activity Recognition Based on ARMA Shape Sequence Modeling
In this paper, we propose a system identification approach for group activity recognition in traffic surveillance. Statistical shape theory is used to extract features, and then...
Ying Wang, Kaiqi Huang, Tieniu Tan
CVPR
2010
IEEE
14 years 2 months ago
Many-to-one Contour Matching for Describing and Discriminating Object Shape
We present an object recognition system that locates an object, identifies its parts, and segments out its contours. A key distinction of our approach is that we use long, salien...
Praveen Srinivasan, Qihui Zhu, Jianbo Shi
PAMI
2012
11 years 11 months ago
Unsupervised Learning of Categorical Segments in Image Collections
Which one comes first: segmentation or recognition? We propose a unified framework for carrying out the two simultaneously and without supervision. The framework combines a fle...
Marco Andreetto, Lihi Zelnik-Manor, Pietro Perona