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Instance classification with prototype selection

Josip Krapac 1 Florent Perronnin 2 Teddy Furon 1 Hervé Jégou 1 
1 TEXMEX - Multimedia content-based indexing
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : We address the problem of instance classification: our goal is to annotate images with tags corresponding to objects classes which exhibit small intra-class variations such as logos, products or landmarks. We propose a novel algorithm for the selection of class-specific prototypes which are used in a voting-based classification scheme. We show significant improvements over two state-of-the-art methods, namely the Fisher vector and Hamming Embedding, on two challenging methods of logos and vehicles.
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Submitted on : Wednesday, February 5, 2014 - 11:56:17 AM
Last modification on : Saturday, November 19, 2022 - 3:43:08 AM
Long-term archiving on: : Sunday, April 9, 2017 - 9:01:13 AM


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  • HAL Id : hal-00942275, version 1


Josip Krapac, Florent Perronnin, Teddy Furon, Hervé Jégou. Instance classification with prototype selection. ICMR - ACM International Conference on Multimedia Retrieval, Apr 2014, Glasgow, United Kingdom. ⟨hal-00942275⟩



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