UOW-Vessel: A Benchmark Dataset of High-Resolution Optical Satellite Images for Vessel Detection and Segmentation

Ly Bui, Son Lam Phung, Yang Di, Thanh Le, Tran Thanh Phong Nguyen, Sandy Burden, Abdesselam Bouzerdoum; Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2024, pp. 4428-4436

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.

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[bibtex]
@InProceedings{Bui_2024_WACV, author = {Bui, Ly and Phung, Son Lam and Di, Yang and Le, Thanh and Nguyen, Tran Thanh Phong and Burden, Sandy and Bouzerdoum, Abdesselam}, title = {UOW-Vessel: A Benchmark Dataset of High-Resolution Optical Satellite Images for Vessel Detection and Segmentation}, booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)}, month = {January}, year = {2024}, pages = {4428-4436} }