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» Learning a Sparse Representation for Object Detection
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CVPR
2009
IEEE
16 years 6 months ago
Discriminative Structure Learning of Hierarchical Representations for Object Detection
A variety of flexible models have been proposed to detect objects in challenging real world scenes. Motivated by some of the most successful techniques, we propose a hierarchica...
Paul Schnitzspan (TU Darmstadt), Mario Fritz (Univ...
89
Voted
ICCV
2009
IEEE
16 years 4 months ago
Learning a dense multi-view representation for detection, viewpoint classification and synthesis of object categories
Recognizing object classes and their 3D viewpoints is an important problem in computer vision. Based on a partbased probabilistic representation [31], we propose a new 3D object...
Hao Su, Min Sun, Li Fei-Fei, Silvio Savarese
CORR
2010
Springer
275views Education» more  CORR 2010»
14 years 11 months ago
Dictionary Optimization for Block-Sparse Representations
Recent work has demonstrated that using a carefully designed dictionary instead of a predefined one, can improve the sparsity in jointly representing a class of signals. This has m...
Kevin Rosenblum, Lihi Zelnik-Manor, Yonina C. Elda...
CLOR
2006
15 years 3 months ago
A Sparse Object Category Model for Efficient Learning and Complete Recognition
We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a weakly-supervised manner: the model is learnt from examp...
Robert Fergus, Pietro Perona, Andrew Zisserman
CORR
2010
Springer
253views Education» more  CORR 2010»
14 years 11 months ago
Fast Inference in Sparse Coding Algorithms with Applications to Object Recognition
Adaptive sparse coding methods learn a possibly overcomplete set of basis functions, such that natural image patches can be reconstructed by linearly combining a small subset of t...
Koray Kavukcuoglu, Marc'Aurelio Ranzato, Yann LeCu...