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Localizing and Orienting Street Views Using Overhead Imagery
[article]
2017
arXiv
pre-print
In this paper we aim to determine the location and orientation of a ground-level query image by matching to a reference database of overhead (e.g. satellite) images. For this task we collect a new dataset with one million pairs of street view and overhead images sampled from eleven U.S. cities. We explore several deep CNN architectures for cross-domain matching -- Classification, Hybrid, Siamese, and Triplet networks. Classification and Hybrid architectures are accurate but slow since they
arXiv:1608.00161v2
fatcat:ost7yhemgzalvio643tw4322eq