Image Retrieval using Multi-scale CNN Features Pooling
- URL: http://arxiv.org/abs/2004.09695v2
- Date: Fri, 24 Apr 2020 11:19:31 GMT
- Title: Image Retrieval using Multi-scale CNN Features Pooling
- Authors: Federico Vaccaro, Marco Bertini, Tiberio Uricchio, Alberto Del Bimbo
- Abstract summary: We present an end-to-end trainable network architecture that exploits a novel multi-scale local pooling based on NetVLAD and a triplet mining procedure based on samples difficulty to obtain an effective image representation.
- Score: 26.811290793232313
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: In this paper, we address the problem of image retrieval by learning images
representation based on the activations of a Convolutional Neural Network. We
present an end-to-end trainable network architecture that exploits a novel
multi-scale local pooling based on NetVLAD and a triplet mining procedure based
on samples difficulty to obtain an effective image representation. Extensive
experiments show that our approach is able to reach state-of-the-art results on
three standard datasets.
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