Saliency-Guided Attention-Based Feature Pyramid Network for Ship Detection in SAR Images
Tianwen Zhang, Xiaoling Zhang, Zikang Shao · 2023
We report a saliency-guided attention-based feature pyramid network (SA-FPN) for ship detection from synthetic aperture radar (SAR) images. The two key contributions are – 1) the saliency-guided technique and 2) the attention-based means. The former offers one unsupervised visual saliency map that can guide FPN to focus more on regions of interest (ROIs). The latter offers one supervised non-local feature self-attention map that can improve FPN’s global representation ability. We offer an effective combination scheme of the two. Experimental results on the open SSDD dataset reveal SA-FPN’s advanced SAR ship detection performance. Furthermore, the ablation studies can confirm the two contributions' effectiveness.