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IJCV
2000
136views more  IJCV 2000»
15 years 6 months ago
A Trainable System for Object Detection
This paper presents a general, trainable system for object detection in unconstrained, cluttered scenes. The system derives much of its power from a representation that describes a...
Constantine Papageorgiou, Tomaso Poggio
CVPR
2011
IEEE
1473views Computer Vision» more  CVPR 2011»
15 years 2 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
PAMI
2012
13 years 9 months ago
CPMC: Automatic Object Segmentation Using Constrained Parametric Min-Cuts
—We present a novel framework to generate and rank plausible hypotheses for the spatial extent of objects in images using bottom-up computational processes and mid-level selectio...
João Carreira, Cristian Sminchisescu
CVPR
2012
IEEE
13 years 9 months ago
The Shape Boltzmann Machine: A strong model of object shape
A good model of object shape is essential in applications such as segmentation, object detection, inpainting and graphics. For example, when performing segmentation, local constra...
S. M. Ali Eslami, Nicolas Heess, John M. Winn
ACL
2006
15 years 8 months ago
URES : an Unsupervised Web Relation Extraction System
Most information extraction systems either use hand written extraction patterns or use a machine learning algorithm that is trained on a manually annotated corpus. Both of these a...
Binyamin Rosenfeld, Ronen Feldman