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Local Deep Descriptors in Bag-of-Words for Image Retrieval
2017
Proceedings of the on Thematic Workshops of ACM Multimedia 2017 - Thematic Workshops '17
The Bag-of-Words (BoW) models using the SIFT descriptors have achieved great success in content-based image retrieval over the past decade. Recent studies show that the neuron activations of the convolutional neural networks (CNN) can be viewed as local descriptors, which can be aggregated into e ective global descriptors for image retrieval. However, little work has been done on using these local deep descriptors in BoW models, especially in the case of large visual vocabularies. In this
doi:10.1145/3126686.3127018
dblp:conf/mm/CaoHS17
fatcat:pudntrtbjnbzpmcsfj2ytplqga