Particular object retrieval with integral max-pooling of CNN activations

@article{Tolias2015ParticularOR,
  title={Particular object retrieval with integral max-pooling of CNN activations},
  author={Giorgos Tolias and Ronan Sicre and Herv{\'e} J{\'e}gou},
  journal={CoRR},
  year={2015},
  volume={abs/1511.05879}
}
Recently, image representation built upon Convolutional Neural Network (CNN) has been shown to provide effective descriptors for image search, outperforming pre-CNN features as short-vector representations. Yet such models are not compatible with geometry-aware re-ranking methods and still outperformed, on some particular object retrieval benchmarks, by traditional image search systems relying on precise descriptor matching, geometric re-ranking, or query expansion. This work revisits both… CONTINUE READING
Highly Influential
This paper has highly influenced 63 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 275 citations. REVIEW CITATIONS
Recent Discussions
This paper has been referenced on Twitter 14 times over the past 90 days. VIEW TWEETS

Topics

Statistics

050100150201620172018
Citations per Year

276 Citations

Semantic Scholar estimates that this publication has 276 citations based on the available data.

See our FAQ for additional information.