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Ship detection using high-resolution remote sensing images is an importanttask, which contribute to sea surface regulation. The complex background andspecial visual angle make ship detection relies in high quality datasets to acertain extent. However, there is few works on giving both preciseclassification and accurate location of ships in existing ship detectiondatasets. To further promote the research of ship detection, we introduced anew fine-grained ship detection datasets, which is named as FGSD. The datasetcollects high-resolution remote sensing images that containing ship samplesfrom multiple large ports around the world. Ship samples were fine categorizedand annotated with both horizontal and rotating bounding boxes. To furtherdetailed the information of the dataset, we put forward a new representationmethod of ships' orientation. For future research, the dock as a new class wasannotated in the dataset. Besides, rich information of images were provided inFGSD, including the source port, resolution and corresponding GoogleEarth' sresolution level of each image. As far as we know, FGSD is the mostcomprehensive ship detection dataset currently and it'll be available soon.Some baselines for FGSD are also provided in this paper.

FGSD: A Dataset for Fine-Grained Ship Detection in High Resolution Satellite Images