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

  • Ly Bui
  • , Son Lam Phung*
  • , Yang Di
  • , Hoang Thanh Le
  • , Tran Thanh Phong Nguyen
  • , Sandy Burden
  • , Abdesselam Bouzerdoum
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Citations (Scopus)

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.

Original languageEnglish
Title of host publication2024 Ieee/cvf Winter Conference On Applications Of Computer Vision, Wacv 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4416-4424
Number of pages9
ISBN (Electronic)9798350318920
ISBN (Print)979-8-3503-1893-7
DOIs
Publication statusPublished - 3 Jan 2024
Event2024 IEEE Winter Conference on Applications of Computer Vision, WACV 2024 - Waikoloa, United States
Duration: 4 Jan 20248 Jan 2024

Publication series

NameIeee Winter Conference On Applications Of Computer Vision

Conference

Conference2024 IEEE Winter Conference on Applications of Computer Vision, WACV 2024
Country/TerritoryUnited States
CityWaikoloa
Period4/01/248/01/24

Keywords

  • Remote-sensing images
  • Shape
  • Ship detection

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