Inria+Xerox@FGcomp: Boosting the Fisher vector for fine-grained classification

Philippe-Henri Gosselin 1, 2 Naila Murray 3 Hervé Jégou 1 Florent Perronnin 3
1 TEXMEX - Multimedia content-based indexing
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : This report describes the joint submission of Inria and Xerox to their participation to the FGCOMP 2013 challenge. Although the proposed system follows most of the standard Fisher classification pipeline, we describe several key features and good practices that improve the accuracy when specifically considering fine-grained classification tasks. In particular, we consider the late fusion of two systems both based on Fisher vectors, but that employ drastically different design choices that make them very complementary. Moreover, we show that a simple yet effective filtering strategy significantly boosts the performance for several class domains.
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Rapport
[Research Report] RR-8431, INRIA. 2013
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https://hal.inria.fr/hal-00920187
Contributeur : Hervé Jégou <>
Soumis le : jeudi 30 janvier 2014 - 10:51:02
Dernière modification le : mercredi 16 mai 2018 - 11:23:05
Document(s) archivé(s) le : dimanche 9 avril 2017 - 02:50:49

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  • HAL Id : hal-00920187, version 2

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Philippe-Henri Gosselin, Naila Murray, Hervé Jégou, Florent Perronnin. Inria+Xerox@FGcomp: Boosting the Fisher vector for fine-grained classification. [Research Report] RR-8431, INRIA. 2013. 〈hal-00920187v2〉

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