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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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Submitted on : Thursday, January 30, 2014 - 10:51:02 AM
Last modification on : Friday, November 18, 2022 - 9:26:59 AM
Long-term archiving on: : Sunday, April 9, 2017 - 2:50:49 AM


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  • HAL Id : hal-00920187, version 2


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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