Unsupervised natural image patch learning

Abstract A metric for natural image patches is an important tool for analyzing images. An efficient means of learning one is to train a deep network to map an image patch to a vector space, in which the Euclidean distance reflects patch similarity. Previous attempts learned such an embedding in a su...

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Bibliographic Details
Main Authors: Dov Danon, Hadar Averbuch-Elor, Ohad Fried, Daniel Cohen-Or
Format: Article
Language:English
Published: SpringerOpen 2019-08-01
Series:Computational Visual Media
Subjects:
Online Access:http://link.springer.com/article/10.1007/s41095-019-0147-y