Learning a Fine Vocabulary

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F10%3A00175516" target="_blank" >RIV/68407700:21230/10:00175516 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Learning a Fine Vocabulary
Original language description
We present a novel similarity measure for bag-of-words type large scale image retrieval. The similarity function is learned in an unsupervised manner, requires no extra space over the standard bag-of-words method and is more discriminative than both L2-based soft assignment and Hamming embedding. Experimentally we show that the novel similarity function achieves mean average precision that is superior to any result published in the literature on the standard Oxford 105k dataset/protocol. At the same time, retrieval with the proposed similarity function is faster than the reference method.
Czech name
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Czech description
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)<br>R - Projekt Ramcoveho programu EK

Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Computer Vision - ECCV 2010, 11th European Conference on Computer Vision, Proceedings, Part III
ISBN
978-3-642-15557-4
ISSN
0302-9743
e-ISSN
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Number of pages
14
Pages from-to
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Publisher name
Springer
Place of publication
Heidelberg
Event location
Heraklion
Event date
Sep 5, 2010
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000286578500001

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