An Anchor-free SAR Ship Detector with Only 1.17M Parameters

An lightweight anchor-free synthetic aperture radar (SAR) ship detector is proposed in this paper. Firstly, According to the SAR image characteristics, ResSARNet with only 0.69M parameters was proposed. Then, with ResSARNet as the backbone network, four improvements have been made to fully convolutional one-stage object detection (FCOS): Center-ness on bounding box regression branch, center sampling, Generalized Intersection over Union (GIoU) loss and adaptive training sample selection (ATSS). To verify the effectiveness of the proposed method, sufficient experiments have been conducted on the widely used SAR Ship Detection Dataset (SSDD). The results show that, the proposed network can achieve 61.5% average precision (AP) and 70.9% average recall (AR) with only 1.17M parameters, which are only 6.5% and 3.2% for [email protected] and [email protected], respectively.