ShipSG: Ship Segmentation and Georeferencing Dataset

The ShipSG dataset is the first public dataset of its kind for ship segmentation and georeferencing. The dataset has been made available for the development and evaluation of instance segmentation and georeferencing methods using computer vision and deep learning, thus advancing the research field of ship recognition for maritime situational awareness.

ShipSG consists of 3,505 images of a port location captured using two different cameras with static and oblique views. In total, 11,625 ship masks, grouped into seven ship classes, were manually annotated. Moreover, each image contains one geographic annotation (latitude and longitude) corresponding to one of the ship masks present in the image.

Terms and Conditions

The dataset is released under the Creative Commons BY-NC-ND 4.0 International license. This means you are free to share, copy, and redistribute the material under the following terms:

Attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made.

NonCommercial – You may not use the material for commercial purposes.

NoDerivatives – If you remix, transform, or build upon the material, you may not distribute the modified material.

No additional restrictions – You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

For attribution and citation of the dataset, please use:

Carrillo-Perez, B.; Barnes, S.; Stephan, M. Ship Segmentation and Georeferencing from Static Oblique View Images. Sensors 2022, 22, 2713. https://doi.org/10.3390/s22072713

The dataset is available upon request. If you require the dataset under a different license that allows commercial use, please contact us.