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» Learning to segment from a few well-selected training images
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ICCV
2005
IEEE
15 years 4 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
15 years 18 days 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
15 years 4 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
16 years 1 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
15 years 5 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. ...