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IROS
2009
IEEE
205views Robotics» more  IROS 2009»
15 years 8 months ago
Probabilistic categorization of kitchen objects in table settings with a composite sensor
— In this paper, we investigate the problem of 3D object categorization of objects typically present in kitchen environments, from data acquired using a composite sensor. Our fra...
Zoltan Csaba Marton, Radu Bogdan Rusu, Dominik Jai...
IJCV
2008
151views more  IJCV 2008»
15 years 1 months ago
Describing Visual Scenes Using Transformed Objects and Parts
We develop hierarchical, probabilistic models for objects, the parts composing them, and the visual scenes surrounding them. Our approach couples topic models originally developed...
Erik B. Sudderth, Antonio Torralba, William T. Fre...
125
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ECCV
2008
Springer
16 years 3 months ago
Weakly Supervised Object Localization with Stable Segmentations
Multiple Instance Learning (MIL) provides a framework for training a discriminative classifier from data with ambiguous labels. This framework is well suited for the task of learni...
Carolina Galleguillos, Boris Babenko, Andrew Rabin...
CVPR
2010
IEEE
15 years 10 months ago
Safety in Numbers: Learning Categories from Few Examples with Multi Model Knowledge Transfer
Learning object categories from small samples is a challenging problem, where machine learning tools can in general provide very few guarantees. Exploiting prior knowledge may be ...
Tatiana Tommasi, Francesco Orabona, Barbara Caputo
104
Voted
IROS
2007
IEEE
128views Robotics» more  IROS 2007»
15 years 8 months ago
Exploiting similarities for robot perception
— A cognitive robot system has to acquire and efficiently store vast knowledge about the world it operates in. To cope with every day tasks, a robot needs to learn, classify and...
Kai Welke, Erhan Oztop, Gordon Cheng, Rüdiger...