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NetVLAD: CNN Architecture for Weakly Supervised Place Recognition
2016
2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
We tackle the problem of large scale visual place recognition, where the task is to quickly and accurately recognize the location of a given query photograph. We present the following three principal contributions. First, we develop a convolutional neural network (CNN) architecture that is trainable in an end-to-end manner directly for the place recognition task. The main component of this architecture, NetVLAD, is a new generalized VLAD layer, inspired by the "Vector of Locally Aggregated
doi:10.1109/cvpr.2016.572
dblp:conf/cvpr/ArandjelovicGTP16
fatcat:5gs4eulzufgxxnq2shhafgytsa