  Ship detection using high-resolution remote sensing images is an important
task, which contribute to sea surface regulation. The complex background and
special visual angle make ship detection relies in high quality datasets to a
certain extent. However, there is few works on giving both precise
classification and accurate location of ships in existing ship detection
datasets. To further promote the research of ship detection, we introduced a
new fine-grained ship detection datasets, which is named as FGSD. The dataset
collects high-resolution remote sensing images that containing ship samples
from multiple large ports around the world. Ship samples were fine categorized
and annotated with both horizontal and rotating bounding boxes. To further
detailed the information of the dataset, we put forward a new representation
method of ships' orientation. For future research, the dock as a new class was
annotated in the dataset. Besides, rich information of images were provided in
FGSD, including the source port, resolution and corresponding GoogleEarth' s
resolution level of each image. As far as we know, FGSD is the most
comprehensive ship detection dataset currently and it'll be available soon.
Some baselines for FGSD are also provided in this paper.
