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In this paper, we introduce a challenging global large-scale ship database(called GLSD), designed specifically for ship detection tasks. The designedGLSD database includes a total of 212,357 annotated instances from 152,576images. Based on the collected images, we propose 13 ship categories thatwidely exist in international routes. These categories include Sailing boat,Fishing boat, Passenger ship, Warship, General cargo ship, Container ship, Bulkcargo carrier, Barge, Ore carrier, Speed boat, Canoe, Oil carrier, and Tug. Themotivations of developing GLSD include the following: 1) providing a refine andextensive ship detection database that benefits the object detection community,2) establishing a database with exhaustive labels (bounding boxes and shipclass categories) in a uniform classification scheme, and 3) providing alarge-scale ship database with geographic information (covering more than 3000ports and 33 routes) that benefits multi-modal analysis. In addition, wediscuss the evaluation protocols corresponding to image characteristics in GLSDand analyze the performance of selected state-of-the-art object detectionalgorithms on GSLD, aiming to establish baselines for future studies. Moreinformation regarding the designed GLSD can be found athttps://github.com/jiaming-wang/GLSD.

GLSD: The Global Large-Scale Ship Database and Baseline Evaluations