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CVPR
2000
IEEE
16 years 4 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
ICCV
2003
IEEE
16 years 4 months ago
A Bayesian Approach to Unsupervised One-Shot Learning of Object Categories
Learning visual models of object categories notoriously requires thousands of training examples; this is due to the diversity and richness of object appearance which requires mode...
Fei-Fei Li 0002, Robert Fergus, Pietro Perona
CVPR
2010
IEEE
15 years 11 months ago
Reading Between The Lines: Object Localization Using Implicit Cues from Image Tags
Current uses of tagged images typically exploit only the most explicit information: the link between the nouns named and the objects present somewhere in the image. We propose to ...
Sung Ju Hwang, University of Texas, Kristen Grauma...
FGCN
2008
IEEE
131views Communications» more  FGCN 2008»
15 years 9 months ago
Object Tracking of Mobile Robot Using Moving Color and Shape Information for the Aged Walking
A mobile robot with various types of sensors via ubiquitous networks is introduced. We designed a mobile robot composed of TCP/IP network, wireless camera and several sensors in a...
Sanghoon Kim, Sangmu Lee, Seungjong Kim
150
Voted
CVPR
2006
IEEE
15 years 8 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. ...