  High-resolution remote sensing images can provide abundant appearance
information for ship detection. Although several existing methods use image
super-resolution (SR) approaches to improve the detection performance, they
consider image SR and ship detection as two separate processes and overlook the
internal coherence between these two correlated tasks. In this paper, we
explore the potential benefits introduced by image SR to ship detection, and
propose an end-to-end network named ShipSRDet. In our method, we not only feed
the super-resolved images to the detector but also integrate the intermediate
features of the SR network with those of the detection network. In this way,
the informative feature representation extracted by the SR network can be fully
used for ship detection. Experimental results on the HRSC dataset validate the
effectiveness of our method. Our ShipSRDet can recover the missing details from
the input image and achieves promising ship detection performance.
