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» Visualizing Diversity and Depth over a Set of Objects
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ICML
2006
IEEE
14 years 8 months ago
Learning user preferences for sets of objects
Most work on preference learning has focused on pairwise preferences or rankings over individual items. In this paper, we present a method for learning preferences over sets of it...
Marie desJardins, Eric Eaton, Kiri Wagstaff
ICRA
2008
IEEE
164views Robotics» more  ICRA 2008»
14 years 2 months ago
Visual servoing set free from image processing
— This paper proposes a new way to achieve robotic tasks by visual servoing. Instead of using geometric features (points, straight lines, pose, homography, etc.) as it is usually...
Christophe Collewet, Éric Marchand, Fran&cc...
CVPR
2011
IEEE
1473views Computer Vision» more  CVPR 2011»
13 years 4 months ago
Object Recognition with Hierarchical Kernel Descriptors
Kernel descriptors provide a unified way to generate rich visual feature sets by turning pixel attributes into patch-level features, and yield impressive results on many object rec...
Liefeng Bo, Kevin Lai, Xiaofeng Ren and Dieter Fox
ICCV
2009
IEEE
15 years 24 days ago
Modeling Deformable Objects from a Single Depth Camera
We propose a novel approach to reconstruct complete 3D deformable models over time by a single depth camera, provided that most parts of the models are observed by the camera at...
Miao Liao, Qing Zhang, Huamin Wang, Ruigang Yang, ...
CVPR
2006
IEEE
14 years 1 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. ...