Efficient Codebook and Factorization for Second Order Representation Learning

Published: Sep 1, 2019
Abstract
Learning rich and compact representations is an open topic in many fields such as object recognition or image retrieval. Deep neural networks have made a major breakthrough during the last few years for these tasks but their representations are not necessary as rich as needed nor as compact as expected. To build richer representations, high order statistics have been exploited and have shown excellent performances, but they produce higher...
Paper Details
Title
Efficient Codebook and Factorization for Second Order Representation Learning
Published Date
Sep 1, 2019
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