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» Learning to segment from a few well-selected training images
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ICCV
2005
IEEE
14 years 2 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
NIPS
2004
13 years 10 months ago
Learning Hyper-Features for Visual Identification
We address the problem of identifying specific instances of a class (cars) from a set of images all belonging to that class. Although we cannot build a model for any particular in...
Andras Ferencz, Erik G. Learned-Miller, Jitendra M...
CVPR
2005
IEEE
14 years 2 months ago
Mapping Low-Level Features to High-Level Semantic Concepts in Region-Based Image Retrieval
In this a novel supervised learning method is proposed to map low-level visualfeatures to high-level semantic conceptsfor region-based image retrieval. The contributions of thispa...
Wei Jiang, Kap Luk Chan, Mingjing Li, HongJiang Zh...
ECCV
2008
Springer
14 years 10 months ago
Automated Delineation of Dendritic Networks in Noisy Image Stacks
We present a novel approach to 3D delineation of dendritic networks in noisy image stacks. We achieve a level of automation beyond that of stateof-the-art systems, which model dend...
Germán González, François Fle...
CVPR
2006
IEEE
14 years 2 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. ...