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» Learning to Detect A Salient Object
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ICCV
2005
IEEE
15 years 7 months ago
Learning Hierarchical Models of Scenes, Objects, and Parts
We describe a hierarchical probabilistic model for the detection and recognition of objects in cluttered, natural scenes. The model is based on a set of parts which describe the e...
Erik B. Sudderth, Antonio B. Torralba, William T. ...
ECCV
2008
Springer
16 years 3 months ago
Multiple Component Learning for Object Detection
Abstract. Object detection is one of the key problems in computer vision. In the last decade, discriminative learning approaches have proven effective in detecting rigid objects, a...
Boris Babenko, Pietro Perona, Piotr Dollár,...
CVPR
2011
IEEE
14 years 9 months ago
Learning to Share Visual Appearance for Multiclass Object Detection
We present a hierarchical classification model that allows rare objects to borrow statistical strength from related objects that have many training examples. Unlike many of the e...
Ruslan Salakhutdinov, Antonio Torralba, Josh Tenen...
ICPR
2008
IEEE
16 years 2 months ago
Scale-invariant medial features based on gradient vector flow fields
We propose a novel set of medial feature interest points based on gradient vector flow (GVF) fields [18]. We exploit the long ranging GVF fields for symmetry estimation by calcula...
Cristóbal Curio, David Engel
ICCV
2005
IEEE
15 years 7 months ago
Contour-Based Learning for Object Detection
We present a novel categorical object detection scheme that uses only local contour-based features. A two-stage, partially supervised learning architecture is proposed: a rudiment...
Jamie Shotton, Andrew Blake, Roberto Cipolla