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» Learning to Recognize Objects from Unseen Modalities
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ICCV
2007
IEEE
15 years 11 months ago
Depth-From-Recognition: Inferring Meta-data by Cognitive Feedback
Thanks to recent progress in category-level object recognition, we have now come to a point where these techniques have gained sufficient maturity and accuracy to succesfully feed...
Alexander Thomas, Vittorio Ferrari, Bastian Leibe,...
IROS
2008
IEEE
129views Robotics» more  IROS 2008»
15 years 4 months ago
Recognizing texture and hardness by touch
Abstract— We have experimented with different neural network based architectures for bio-inspired self-organizing texture and hardness perception systems. To this end we have dev...
Magnus Johnsson, Christian Balkenius
77
Voted
ICCV
2009
IEEE
16 years 2 months ago
Learning a dense multi-view representation for detection, viewpoint classification and synthesis of object categories
Recognizing object classes and their 3D viewpoints is an important problem in computer vision. Based on a partbased probabilistic representation [31], we propose a new 3D object...
Hao Su, Min Sun, Li Fei-Fei, Silvio Savarese
IROS
2009
IEEE
205views Robotics» more  IROS 2009»
15 years 4 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...
CVPR
2010
IEEE
15 years 3 months ago
Recognizing Human Actions from Still Images with Latent Poses
We consider the problem of recognizing human actions from still images. We propose a novel approach that treats the pose of the person in the image as latent variables that will h...
Weilong Yang, Yang Wang, Greg Mori