YFCC100M-HNfc6: A Large-Scale Deep Features Benchmark for Similarity Search

  • Giuseppe Amato
  • Fabrizio Falchi
  • Claudio Gennaro
  • Fausto Rabitti
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9939)

Abstract

In this paper, we present YFCC100M-HNfc6, a benchmark consisting of 97M deep features extracted from the Yahoo Creative Commons 100M (YFCC100M) dataset. Three type of features were extracted using a state-of-the-art Convolutional Neural Network trained on the ImageNet and Places datasets. Together with the features, we made publicly available a set of 1,000 queries and k-NN results obtained by sequential scan. We first report detailed statistical information on both the features and search results. Then, we show an example of performance evaluation, performed using this benchmark, on the MI-File approximate similarity access method.

Keywords

Similarity search Deep features Content-based image retrieval Convolutional neural networks YFCC100M 

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Giuseppe Amato
    • 1
  • Fabrizio Falchi
    • 1
  • Claudio Gennaro
    • 1
  • Fausto Rabitti
    • 1
  1. 1.ISTI-CNRPisaItaly

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