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» Objective Functions for Feature Discrimination
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ECCV
2008
Springer
16 years 2 months ago
Hierarchical Support Vector Random Fields: Joint Training to Combine Local and Global Features
Abstract. Recently, impressive results have been reported for the detection of objects in challenging real-world scenes. Interestingly however, the underlying models vary greatly e...
Paul Schnitzspan, Mario Fritz, Bernt Schiele
CVPR
2010
IEEE
15 years 9 months ago
Learning Mid-Level Features For Recognition
Many successful models for scene or object recognition transform low-level descriptors (such as Gabor filter responses, or SIFT descriptors) into richer representations of interme...
Y-Lan Boureau, Francis Bach, Yann LeCun, Jean Ponc...
90
Voted
ICIP
2009
IEEE
14 years 10 months ago
Cat face detection with two heterogeneous features
In this paper, we propose a generic and efficient object detection framework based on two heterogeneous features and demonstrate effectiveness of our method for a cat face detecti...
Tatsuo Kozakaya, Satoshi Ito, Susumu Kubota, Osamu...
ICCV
2009
IEEE
16 years 5 months ago
Quantifying Contextual Information for Object Detection
Context is critical for minimising ambiguity in object de- tection. In this work, a novel context modelling framework is proposed without the need of any prior scene segmen- tat...
Wei-Shi Zheng, Shaogang Gong and Tao Xiang
77
Voted
IJCV
2011
109views more  IJCV 2011»
14 years 7 months ago
Measuring and Predicting Object Importance
How important is a particular object in a photograph of a complex scene? We propose a definition of importance and present two methods for measuring object importance from human o...
Merrielle Spain, Pietro Perona