NWPU VHR-10 dataset

NWPU VHR-10 dataset is a publicly available 10-class geospatial object detection dataset used for research purposes only. These ten classes of objects are airplane, ship, storage tank, baseballdiamond, tennis court, basketball court, ground track field, harbor, bridge, and vehicle. This dataset contains totally 800 very-high-resolution (VHR) remote sensing images that were cropped from Google Earth and Vaihingen dataset and then manually annotated by experts.


Please cite the following relevant papers when publishing results that use this dataset fully or partly:

[1] Gong Cheng, Junwei Han, Peicheng Zhou, Lei Guo. Multi-class geospatial object detection and geographic image classification based on collection of part detectors. ISPRS Journal of Photogrammetry and Remote Sensing, 98: 119-132, 2014.

[2] Gong Cheng, Junwei Han. A survey on object detection in optical remote sensing images. ISPRS Journal of Photogrammetry and Remote Sensing, 117: 11-28, 2016.

[3] Gong Cheng, Peicheng Zhou, Junwei Han. Learning rotation-invariant convolutional neural networks for object detection in VHR optical remote sensing images. IEEE Transactions on Geoscience and Remote Sensing, 54(12): 7405-7415, 2016.


This dataset can be downloaded from OneDrive or BaiduWangpan.



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