Remote sensing image retrieval (RSIR) aims to search and retrieve the images of interest
from a large remote sensing image archive, which has remained to be a hot topic over the …

Three-dimensional mapping is an increasingly important feature for recent photogrammetry
and remote sensing (RS) systems. Currently, unmanned aerial vehicles (UAVs) have …

The dominant CNN-based methods for cross-view image geo-localization rely on polar
transform and fail to model global correlation. We propose a pure transformer-based …

Humans can orient themselves in their 3D environments using simple 2D maps. Differently,
algorithms for visual localization mostly rely on complex 3D point clouds that are expensive …

The blooming proliferation of aeronautics and astronautics platforms, together with the ever-
increasing remote sensing imaging sensors on these platforms, has led to the formation of …

In this work, we address the problem of cross-view geo-localization, which estimates the
geospatial location of a street view image by matching it with a database of geo-tagged …

The goal of cross-view image based geo-localization is to determine the location of a given
street view image by matching it against a collection of geo-tagged satellite images. This …

Cross-view geo-localization is to spot images of the same geographic target from different
platforms, eg, drone-view cameras and satellites. It is challenging in the large visual …

This paper addresses the problem of vehicle-mounted camera localization by matching a
ground-level image with an overhead-view satellite map. Existing methods often treat this …

Cross-view image geo-localization aims to determine the locations of street-view query
images by matching with GPS-tagged reference images from aerial view. Recent works …