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» Learning Models for Object Recognition
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ICCV
2003
IEEE
15 years 3 days ago
Object Recognition with Informative Features and Linear Classification
In this paper we show that efficient object recognition can be obtained by combining informative features with linear classification. The results demonstrate the superiority of in...
Michel Vidal-Naquet, Shimon Ullman
ESANN
2006
13 years 11 months ago
Iterative context compilation for visual object recognition
This contribution describes an almost parameterless iterative context compilation method, which produces feature layers, that are especially suited for mixed bottom-up top-down ass...
Jens Teichert, Rainer Malaka
CVPR
2011
IEEE
1473views Computer Vision» more  CVPR 2011»
13 years 6 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
2011
IEEE
12 years 10 months ago
Relative Attributes
Human-nameable visual “attributes” can benefit various recognition tasks. However, existing techniques restrict these properties to categorical labels (for example, a person ...
Devi Parikh, Kristen Grauman
CVPR
2010
IEEE
14 years 3 months ago
Object Recognition as Ranking Holistic Figure-Ground Hypotheses
We present an approach to visual object-class recognition and segmentation based on a pipeline that combines multiple, holistic figure-ground hypotheses generated in a bottom-up,...
Fuxin Li, JoãCarreira, Cristian Sminchisescu