This repository contains the dataset link and the code for our paper University-1652: A Multi-view Multi-source Benchmark for Drone-based Geo-localization. We collect 1652 buildings of 72 universities around the world. Thank you for your kindly attention.

Task 1: Drone-view target localization. (Drone -> Satellite) Given one drone-view image or video, the task aims to find the most similar satellite-view image to localize the target building in the satellite view.

Task 2: Drone navigation. (Satellite -> Drone) Given one satellite-view image, the drone intends to find the most relevant place (drone-view images) that it has passed by. According to its flight history, the drone could be navigated back to the target place.

about Dataset

The dataset split is as follows:

Citation

The following paper uses and reports the result of the baseline model. You may cite it in your paper.

 @article{zheng2020university,
  title={University-1652: A Multi-view Multi-source Benchmark for Drone-based Geo-localization},
  author={Zheng, Zhedong and Wei, Yunchao and Yang, Yi},
  journal={ACM Multimedia},
  year={2020}
    } 

Instance loss is defined in

@article{zheng2017dual,
title={Dual-Path Convolutional Image-Text Embeddings with Instance Loss},
author={Zheng, Zhedong and Zheng, Liang and Garrett, Michael and Yang, Yi and Xu, Mingliang and Shen, Yi-Dong},
journal={ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM)},
doi={10.1145/3383184},
volume={16},
number={2},
pages={1--23},
year={2020},
publisher={ACM New York, NY, USA}
}