UOW-Vessel: A Benchmark Dataset of High-Resolution Optical Satellite Images for Vessel Detection and Segmentation
Abstract
In this paper, we introduce UOW-Vessel, a benchmark dataset of high-resolution optical satellite images for vessel detection and segmentation. Our dataset consists of 3,500 images, collected from 14 countries across 4 continents. With a total of 35,598 instances in 10 vessel categories, UOW-Vessel is to date the largest satellite image dataset for vessel recognition. Furthermore, compared to the existing public datasets that only provide bounding box ground-truth, our new dataset offers more accurate polygon annotations of vessel objects. This dataset is expected to support instance segmentation-based approaches, which is a less investigated area in vessel surveillance. We also report extensive evaluations of the recent algorithms for instance segmentation on the new benchmark dataset.
Cite
Text
Bui et al. "UOW-Vessel: A Benchmark Dataset of High-Resolution Optical Satellite Images for Vessel Detection and Segmentation." Winter Conference on Applications of Computer Vision, 2024.Markdown
[Bui et al. "UOW-Vessel: A Benchmark Dataset of High-Resolution Optical Satellite Images for Vessel Detection and Segmentation." Winter Conference on Applications of Computer Vision, 2024.](https://mlanthology.org/wacv/2024/bui2024wacv-uowvessel/)BibTeX
@inproceedings{bui2024wacv-uowvessel,
title = {{UOW-Vessel: A Benchmark Dataset of High-Resolution Optical Satellite Images for Vessel Detection and Segmentation}},
author = {Bui, Ly and Phung, Son Lam and Di, Yang and Le, Thanh and Nguyen, Tran Thanh Phong and Burden, Sandy and Bouzerdoum, Abdesselam},
booktitle = {Winter Conference on Applications of Computer Vision},
year = {2024},
pages = {4428-4436},
url = {https://mlanthology.org/wacv/2024/bui2024wacv-uowvessel/}
}