The ShipSG dataset is the first public dataset of its kind for ship segmentation and georeferencing. It is designed for the development and evaluation of instance segmentation and georeferencing methods using computer vision and deep learning, contributing to the research field of ship recognition for maritime situational awareness.
ShipSG consists of:
- 3,505 images of a port location captured with two different cameras (static and oblique views).
- 11,625 manually annotated ship masks, categorized into seven ship classes.
- Geographic annotations (latitude and longitude) for one ship per image.
The dataset is released under the Creative Commons BY-NC-ND 4.0 International license. You may:
- Share: Copy and redistribute the material in any medium or format.
- Attribution: You must give appropriate credit 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 impose legal terms that prevent others from doing what the license permits.
For citation, please use:
Carrillo-Perez, B.; Barnes, S.; Stephan, M. Ship Segmentation and Georeferencing from Static Oblique View Images. Sensors 2022, 22, 2713. DOI: https://doi.org/10.3390/s22072713
The dataset is publicly available for download under request. To request access:
- Go to the Zenodo dataset page:
- Click "Request Access" on the dataset page.
- Agree to the license terms.
- Your request will be reviewed, and if approved, you will receive access via Zenodo.
If you need the dataset under a different license (e.g., for commercial use), please contact us via Zenodo.