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choyaa
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PiLoT-data

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uav-geolocalization
navigation
drone-imagery
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Dataset Card for PiLoT Dataset

Total Size: Approximately 5-6 TB.
Status: ⏳ Uploading... (The dataset is currently being synchronized to the cloud drives. Some links may become available shortly.)

Trajectory Card

  • Ref-Query Pairs: Each sub-dataset includes a Reference (clear weather) and a Query (with weather effects) trajectory following the exact same path.
  • Data Modalities: Sequential frames are provided as *_0.png for RGB and *_1.png for Metric Depth.
  • Data Access:
    • Images: Download from the cloud drive links in the README.
    • Poses & Cameras: Download directly from this repository.
  • 🙋❗Note: Please download the reprojection code from this repo and run the demo first to verify the projection alignment and coordinate system.
Trajectory Name Location (City, Country) Lat / Lng Height Pitch Range 🔴 Baidu Netdisk 🔵 Google Drive
England_seq1@200@30_50 Oxford, UK 51.7345 / -1.2715 200m [30, 50] Link Link
England_seq2@300@0_30 Oxford, UK 51.7653 / -1.2976 300m [0, 30] Link Link
England_seq3@500@30_50 Manchester, UK 53.4687 / -2.2627 500m [30, 50] Link Link
England_seq4@200@0_30 Manchester, UK 53.4846 / -2.2256 200m [0, 30] Link Link
England_seq5@500@30_50 Manchester, UK 53.4689 / -2.3649 500m [30, 50] Link Link
England_seq6@300@30_50 Coventry, UK 52.3789 / -1.5969 300m [30, 50] Link Link
England_seq8@300@30_50 London, UK 51.5401 / -0.1380 300m [30, 50] Link Link
England_seq9@500@0_30 London, UK 51.5830 / -0.2213 500m [0, 30] Link Link
England_seq10@200@30_50 Cambridge, UK 52.1964 / 0.0950 200m [30, 50] Link Link
Finnish_seq1@200@30_50 Helsinki, Finland 60.1477 / 24.9221 200m [30, 50] Link Link
Finnish_seq2@300@0_30 Helsinki, Finland 60.1913 / 24.9066 300m [0, 30] Link Link
Finnish_seq4@200@0_30 Espoo, Finland 60.2041 / 24.7858 200m [0, 30] Link Link
Finnish_seq5@500@30_50 Turku, Finland 60.4387 / 22.2074 500m [30, 50] Link Link
Finnish_seq6@300@30_50 Turku, Finland 60.4617 / 22.2642 300m [30, 50] Link Link
Finnish_seq8@300@30_50 Tampere, Finland 61.5100 / 23.7607 300m [30, 50] Link Link
Finnish_seq10@200@30_50 Vantaa, Finland 60.3131 / 25.0673 200m [30, 50] Link Link
France_seq1@200@30_50 Paris, France 48.8460 / 2.3116 200m [30, 50] Link Link
France_seq2@300@0_30 Paris, France 48.8724 / 2.2739 300m [0, 30] Link Link
France_seq4@200@0_30 Roissy-en-France, France 49.0151 / 2.5308 200m [0, 30] Link Link
France_seq5@500@30_50 Paris, France 48.8805 / 2.3694 500m [30, 50] Link Link
France_seq8@300@30_50 Metz, France 49.1235 / 6.1455 300m [30, 50] Link Link
France_seq9@500@0_30 Bordeaux, France 44.8501 / -0.5819 500m [0, 30] Link Link
France_seq10@200@30_50 Marseille, France 43.3191 / 5.3817 200m [30, 50] Link Link
German_seq1@200@30_50 Munich, Germany 48.1544 / 11.5428 200m [30, 50] Link Link
German_seq2@300@0_30 Aachen, Germany 50.7750 / 6.0724 300m [0, 30] Link Link
German_seq4@200@0_30 Munich, Germany 48.1877 / 11.5741 200m [0, 30] Link Link
German_seq5@500@30_50 Frankfurt, Germany 50.0439 / 8.5277 500m [30, 50] Link Link
German_seq8@300@30_50 Berlin, Germany 52.4975 / 13.3710 300m [30, 50] Link Link
German_seq9@500@0_30 Frankfurt, Germany 50.1100 / 8.6641 500m [0, 30] Link Link
German_seq10@200@30_50 Heidelberg, Germany 49.4041 / 8.6462 200m [30, 50] Link Link
Italy_seq1@200@30_50 Milan, Italy 45.4467 / 9.2271 200m [30, 50] Link Link
Italy_seq2@300@0_30 Milan, Italy 45.4910 / 9.1526 300m [0, 30] Link Link
Italy_seq3@500@30_50 Rome, Italy 41.9260 / 12.4894 500m [30, 50] Link Link
Italy_seq4@200@0_30 Rome, Italy 41.9161 / 12.4628 200m [0, 30] Link Link
Italy_seq5@500@30_50 Bologna, Italy 44.4906 / 11.3297 500m [30, 50] Link Link
Italy_seq6@300@30_50 Bologna, Italy 44.4776 / 11.3755 300m [30, 50] Link Link
Italy_seq8@300@30_50 Florence, Italy 43.8488 / 11.1064 300m [30, 50] Link Link
Italy_seq9@500@0_30 Venice, Italy 45.4405 / 12.3005 500m [0, 30] Link Link
Netherland_seq1@500@0_30 Amsterdam, Netherlands 52.3492 / 4.8506 500m [0, 30] Link Link
Netherland_seq4@200@30_50 Amsterdam, Netherlands 52.3391 / 4.8653 200m [30, 50] Link Link
Netherland_seq5@300@0_30 The Hague, Netherlands 52.0709 / 4.2502 300m [0, 30] Link Link
Netherland_seq7@200@0_30 Delft, Netherlands 51.9898 / 4.3614 200m [0, 30] Link Link
Netherland_seq8@500@30_50 Schiphol, Netherlands 52.3203 / 4.7171 500m [30, 50] Link Link
Netherland_seq9@300@30_50 Maastricht, Netherlands 50.8688 / 5.6485 300m [30, 50] Link Link
Netherland_seq10@200@0_30 Tilburg, Netherlands 51.5559 / 5.0494 200m [0, 30] Link Link
spain_seq1@500@0_30 Barcelona, Spain 41.3697 / 2.1916 500m [0, 30] Link Link
spain_seq2@300@30_50 Barcelona, Spain 41.3544 / 2.1485 300m [30, 50] Link Link
spain_seq3@300@30_50 Valencia, Spain 39.4519 / -0.3441 300m [30, 50] Link Link
spain_seq4@500@30_50 Valencia, Spain 39.4604 / -0.3035 500m [30, 50] Link Link
spain_seq5@200@30_50 Madrid, Spain 40.5479 / -3.7035 200m [30, 50] Link Link
spain_seq6@200@0_30 Madrid, Spain 40.4163 / -3.7145 200m [0, 30] Link Link
spain_seq8@500@0_30 San Sebastián, Spain 43.3251 / -1.9178 500m [0, 30] Link Link
spain_seq9@300@30_50 Seville, Spain 37.3611 / -6.0668 300m [30, 50] Link Link
Switzerland_seq1@500@30_50 Lausanne, Switzerland 46.5368 / 6.5305 500m [30, 50] Link Link
Switzerland_seq2@200@0_30 Basel, Switzerland 47.6281 / 7.5723 200m [0, 30] Link Link
Switzerland_seq3@300@30_50 Zurich, Switzerland 47.3749 / 8.5493 300m [30, 50] Link Link
Switzerland_seq5@300@0_30 Lausanne, Switzerland 46.5178 / 6.5259 300m [0, 30] Link Link
Switzerland_seq6@200@30_50 Lausanne, Switzerland 46.5087 / 6.5445 200m [30, 50] Link Link
Switzerland_seq7@500@30_50 Geneva, Switzerland 43.3265 / -1.9552 500m [30, 50] Link Link
Switzerland_seq8@300@30_50 Geneva, Switzerland 43.3251 / -1.9178 300m [30, 50] Link Link
Switzerland_seq9@500@30_50 Bern, Switzerland 37.3611 / -6.0668 500m [30, 50] Link Link
Switzerland_seq10@200@0_30 Bern, Switzerland 37.3685 / -6.0130 200m [0, 30] Link Link
Switzerland_seq12@300@0_30 Lucerne, Switzerland 47.0303 / 8.2557 300m [0, 30] Link Link
Switzerland_seq13@500@0_30 Lucerne, Switzerland 47.0536 / 8.2621 500m [0, 30] Link Link
Switzerland_seq14@200@0_30 Lucerne, Switzerland 47.0897 / 8.2462 200m [0, 30] Link Link
Switzerland_seq16@300@30_50 Zurich, Switzerland 47.3534 / 8.5334 300m [30, 50] Link Link
Switzerland_seq17@200@0_30 Zurich, Switzerland 47.3876 / 8.5052 200m [0, 30] Link Link
Switzerland_seq18@300@30_50 Zurich, Switzerland 47.3971 / 8.5259 300m [30, 50] Link Link
Switzerland_seq19@500@0_30 Zurich, Switzerland 47.3894 / 8.4962 500m [0, 30] Link Link
Switzerland_seq20@200@30_50 Zurich, Switzerland 47.4094 / 8.4573 200m [30, 50] Link Link
Switzerland_seq21@200@30_50 Geneva, Switzerland 46.2181 / 6.1262 200m [30, 50] Link Link
Switzerland_seq22@300@0_30 Geneva, Switzerland 46.2271 / 6.1392 300m [0, 30] Link Link
Switzerland_seq23@500@0_30 Geneva, Switzerland 46.2002 / 6.1098 500m [0, 30] Link Link
Switzerland_seq24@200@0_30 Geneva, Switzerland 46.1817 / 6.0968 200m [0, 30] Link Link
Switzerland_seq25@500@30_50 Bern, Switzerland 46.9171 / 7.4149 500m [30, 50] Link Link
Switzerland_seq26@300@30_50 Bern, Switzerland 46.9410 / 7.3823 300m [30, 50] Link Link
Switzerland_seq27@200@0_30 Bern, Switzerland 46.9316 / 7.4421 200m [0, 30] Link Link
Switzerland_seq28@300@30_50 St. Gallen, Switzerland 47.4465 / 9.4201 300m [30, 50] Link Link
Switzerland_seq29@500@0_30 Winterthur, Switzerland 47.4770 / 8.7008 500m [0, 30] Link Link
Switzerland_seq30@200@30_50 Winterthur, Switzerland 47.5307 / 8.7592 200m [30, 50] Link Link
Switzerland_seq31@200@30_50 Winterthur, Switzerland 47.4933 / 8.7005 200m [30, 50] Link Link
Switzerland_seq32@300@0_30 Winterthur, Switzerland 47.5323 / 8.6611 300m [0, 30] Link Link
Switzerland_seq33@500@0_30 Fribourg, Switzerland 46.8333 / 7.1405 500m [0, 30] Link Link
Switzerland_seq34@200@0_30 Fribourg, Switzerland 46.8096 / 7.1637 200m [0, 30] Link Link
Switzerland_seq35@500@30_50 Neuchâtel, Switzerland 46.9911 / 6.9122 500m [30, 50] Link Link
Switzerland_seq36@300@30_50 Biel, Switzerland 47.1306 / 7.2319 300m [30, 50] Link Link
Switzerland_seq37@200@0_30 Biel, Switzerland 47.1235 / 7.2386 200m [0, 30] Link Link
Switzerland_seq38@300@30_50 Biel, Switzerland 47.1100 / 7.2220 300m [30, 50] Link Link
Switzerland_seq39@500@0_30 Lugano, Switzerland 45.9913 / 8.9424 500m [0, 30] Link Link
Switzerland_seq40@200@30_50 Thun, Switzerland 46.7695 / 7.6109 200m [30, 50] Link Link
Switzerland_seq43@500@0_30 Meyrin, Switzerland 46.2205 / 6.0477 500m [0, 30] Link Link
Switzerland_seq44@200@0_30 Lausanne, Switzerland 46.5432 / 6.5679 200m [0, 30] Link Link
Switzerland_seq45@500@30_50 Lugano, Switzerland 45.9938 / 8.9081 500m [30, 50] Link Link
Switzerland_seq46@300@30_50 Schaffhausen, Switzerland 47.7004 / 8.6137 300m [30, 50] Link Link
Switzerland_seq47@200@0_30 Schaffhausen, Switzerland 47.7230 / 8.6519 200m [0, 30] Link Link
Switzerland_seq48@300@30_50 Schaffhausen, Switzerland 47.6934 / 8.6037 300m [30, 50] Link Link
Switzerland_seq49@500@0_30 Sion, Switzerland 46.2320 / 7.3857 500m [0, 30] Link Link
Switzerland_seq50@200@30_50 Zug, Switzerland 47.1853 / 8.5280 200m [30, 50] Link Link
Switzerland_seq51@200@30_50 Zug, Switzerland 47.1870 / 8.4719 200m [30, 50] Link Link
Switzerland_seq52@300@0_30 Zug, Switzerland 47.2009 / 8.4735 300m [0, 30] Link Link
Switzerland_seq53@500@0_30 Solothurn, Switzerland 47.1969 / 7.5088 500m [0, 30] Link Link
USA_seq1@200@0_30 Chicago, USA 41.8891 / -87.6396 200m [0, 30] Link Link
USA_seq3@500@0_30 Las Vegas, USA 36.0927 / -115.1618 500m [0, 30] Link Link
USA_seq5@500@0_30 New York, USA 40.7302 / -73.9710 500m [0, 30] Link Link
USA_seq6@300@30_50 San Francisco, USA 37.7739 / -122.3873 300m [30, 50] Link Link
USA_seq10@200@0_30 Washington D.C., USA 38.8798 / -76.9822 200m [0, 30] Link Link

Citation

If you find this dataset useful, please cite our CVPR 2026 Highlight paper:

@article{choya2026pilot,
  title={PiLoT: Neural Pixel-to-3D Registration for UAV-based Ego and Target Geo-localization},
  author={Your Name and Others},
  journal={arXiv preprint arXiv:2603.20778},
  year={2026}
}

Licensing Information

Copyright (c) 2026 Saw Lab, National University of Defense Technology (NUDT).

The Dataset is provided for non-commercial research and educational purposes only.

Terms of Use:

  • Attribution: You must provide appropriate credit to Saw Lab, NUDT and cite the corresponding CVPR 2026 paper in any derivative works or publications.
  • Non-Commercial: Commercial use, including but not limited to selling the data or using it to train commercial models, is strictly prohibited.
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