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 …

In this paper, we introduce a novel approach to fine-grained cross-view geo-localization. Our
method aligns a warped ground image with a corresponding GPS-tagged satellite image …

This work addresses cross-view camera pose estimation, ie, determining the 3-Degrees-of-
Freedom camera pose of a given ground-level image wrt an aerial image of the local area …

Given a ground-level query image and a geo-referenced aerial image that covers the
query's local surroundings, fine-grained cross-view localization aims to estimate the location …

Cross-view geolocalization identifies the geographic location of street view images by
matching them with a georeferenced satellite database. Significant challenges arise due to …

This paper investigates the effective utilization of unlabeled data for large-area cross-view
geo-localization (CVGL) encompassing both unsupervised and semi-supervised settings …

Unmanned Aerial Vehicles (UAVs), also known as drones, have become increasingly
popular in recent years due to their ability to capture high-quality multimedia data from the …

Street-view imagery provides us with novel experiences to explore different places remotely.
Carefully calibrated street-view images (eg, Google Street View) can be used for different …

Traditional approaches for learning on categorical data underexploit the dependencies
between columns (aka fields) in a dataset because they rely on the embedding of data …

Cross-view geo-localization is a critical task in various applications, such as smart city
management and disaster monitoring. Current methods typically divide a satellite image into …