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» Objective Functions for Feature Discrimination
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ECCV
2008
Springer
16 years 8 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
16 years 2 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...
ICIP
2009
IEEE
15 years 3 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 11 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
IJCV
2011
109views more  IJCV 2011»
15 years 1 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