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118
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CVPR
2012
IEEE
13 years 1 months ago
Large scale metric learning from equivalence constraints
In this paper, we raise important issues on scalability and the required degree of supervision of existing Mahalanobis metric learning methods. Often rather tedious optimization p...
Martin Köstinger, Martin Hirzer, Paul Wohlhar...
107
Voted
CVPR
2009
IEEE
16 years 6 months ago
Contextual Classification with Functional Max-Margin Markov Networks
We address the problem of label assignment in computer vision: given a novel 3-D or 2-D scene, we wish to assign a unique label to every site (voxel, pixel, superpixel, etc.). To...
Daniel Munoz, James A. Bagnell, Martial Hebert, Ni...
ICML
2005
IEEE
15 years 11 months ago
Action respecting embedding
Dimensionality reduction is the problem of finding a low-dimensional representation of highdimensional input data. This paper examines the case where additional information is kno...
Michael H. Bowling, Ali Ghodsi, Dana F. Wilkinson
ICML
2003
IEEE
15 years 11 months ago
Learning Metrics via Discriminant Kernels and Multidimensional Scaling: Toward Expected Euclidean Representation
Distance-based methods in machine learning and pattern recognition have to rely on a metric distance between points in the input space. Instead of specifying a metric a priori, we...
Zhihua Zhang
91
Voted
3DPVT
2002
IEEE
146views Visualization» more  3DPVT 2002»
15 years 3 months ago
Geometry of Contour-based Correspondence for Stereo
We consider the problem of computing stereo correspondence for scenes dense in physical structure, such as a bouquet of flowers. Boundaries are then space curves, formally govern...
Steven W. Zucker, Gang Li