For image retrieval methods based on bag of visual words, much attention has been paid to
enhancing the discriminative powers of the local features. Although retrieved images are …

In the large-scale image retrieval task, the two most important requirements are the
discriminability of image representations and the efficiency in computation and storage of …

In image retrieval, deep local features learned in a data-driven manner have been
demonstrated effective to improve retrieval performance. To realize efficient retrieval on …

Several recent works have shown that image descriptors produced by deep convolutional
neural networks provide state-of-the-art performance for image classification and retrieval …

Convolutional Neural Network (CNN) is a very powerful approach to extract discriminative
local descriptors for effective image search. Recent work adopts fine-tuned strategies to …

Recent attempts on the Convolutional Neural Network (CNN) based image retrieval usually
adopt the output of a specific convolutional or fully connected layer as feature …

Image retrieval is the task of finding all images in the database that are similar to a query
image. Two types of image representations have been studied to address this task: global …

Several recent works have shown that image descriptors produced by deep convolutional
neural networks provide state-of-the-art performance for image classification and retrieval …

It has been shown that image descriptors extracted by convolutional neural networks
(CNNs) achieve remarkable results for retrieval problems. In this paper, we apply attention …

Recent studies in image retrieval task have shown that ensembling different models and
combining multiple global descriptors lead to performance improvement. However, training …