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University-1652 全球72所大学的1652座建筑物数据

University-1652 全球72所大学的1652座建筑物数据

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This repository contains the dataset link and the code for our paper University-1652: A Multi-view Multi-source Benchmar......

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    * 以上分析是由系统提取分析形成的结果,具体实际数据为准。

    README.md

    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:

    Split #imgs #classes #universities
    Training 50,218 701 33
    Query_drone 37,855 701 39
    Query_satellite 701 701 39
    Query_ground 2,579 701 39
    Gallery_drone 51,355 951 39
    Gallery_satellite 951 951 39
    Gallery_ground 2,921 793 39

    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}
    }

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