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» Image distance functions for manifold learning
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TSMC
2010
14 years 4 months ago
Distance Approximating Dimension Reduction of Riemannian Manifolds
We study the problem of projecting high-dimensional tensor data on an unspecified Riemannian manifold onto some lower dimensional subspace1 without much distorting the pairwise geo...
Changyou Chen, Junping Zhang, Rudolf Fleischer
CVPR
2008
IEEE
15 years 4 months ago
Learning a geometry integrated image appearance manifold from a small training set
While low-dimensional image representations have been very popular in computer vision, they suffer from two limitations: (i) they require collecting a large and varied training se...
Yilei Xu, Amit K. Roy Chowdhury
ICCV
2007
IEEE
15 years 11 months ago
Learning Globally-Consistent Local Distance Functions for Shape-Based Image Retrieval and Classification
We address the problem of visual category recognition by learning an image-to-image distance function that attempts to satisfy the following property: the distance between images ...
Andrea Frome, Yoram Singer, Fei Sha, Jitendra Mali...
CVPR
2004
IEEE
15 years 11 months ago
Learning Distance Functions for Image Retrieval
Image retrieval critically relies on the distance function used to compare a query image to images in the database. We suggest to learn such distance functions by training binary ...
Tomer Hertz, Aharon Bar-Hillel, Daphna Weinshall
87
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CVPR
2006
IEEE
15 years 11 months ago
Dimensionality Reduction by Learning an Invariant Mapping
Dimensionality reduction involves mapping a set of high dimensional input points onto a low dimensional manifold so that "similar" points in input space are mapped to ne...
Raia Hadsell, Sumit Chopra, Yann LeCun