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» Learning Models for Object Recognition
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CVPR
2009
IEEE
14 years 3 months ago
Manifold Discriminant Analysis
This paper presents a novel discriminative learning method, called Manifold Discriminant Analysis (MDA), to solve the problem of image set classification. By modeling each image s...
Ruiping Wang, Xilin Chen
CVPR
2006
IEEE
14 years 3 months ago
Depth from Familiar Objects: A Hierarchical Model for 3D Scenes
We develop an integrated, probabilistic model for the appearance and three-dimensional geometry of cluttered scenes. Object categories are modeled via distributions over the 3D lo...
Erik B. Sudderth, Antonio B. Torralba, William T. ...
JMLR
2010
192views more  JMLR 2010»
13 years 3 months ago
Efficient Learning of Deep Boltzmann Machines
We present a new approximate inference algorithm for Deep Boltzmann Machines (DBM's), a generative model with many layers of hidden variables. The algorithm learns a separate...
Ruslan Salakhutdinov, Hugo Larochelle
CAIP
2009
Springer
211views Image Analysis» more  CAIP 2009»
14 years 3 months ago
Contextual-Guided Bag-of-Visual-Words Model for Multi-class Object Categorization
Abstract. Bag-of-words model (BOW) is inspired by the text classification problem, where a document is represented by an unsorted set of contained words. Analogously, in the objec...
Mehdi Mirza-Mohammadi, Sergio Escalera, Petia Rade...
ECCV
2008
Springer
14 years 11 months ago
Learning Spatial Context: Using Stuff to Find Things
The sliding window approach of detecting rigid objects (such as cars) is predicated on the belief that the object can be identified from the appearance in a small region around the...
Geremy Heitz, Daphne Koller