Saliency-Guided Attention-Based Feature Pyramid Network for Ship Detection in SAR Images
- Resource Type
- Conference
- Authors
- Zhang, Tianwen; Zhang, Xiaoling; Shao, Zikang
- Source
- IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium Geoscience and Remote Sensing Symposium, IGARSS 2023 - 2023 IEEE International. :4950-4953 Jul, 2023
- Subject
- Aerospace
Components, Circuits, Devices and Systems
Fields, Waves and Electromagnetics
Geoscience
Signal Processing and Analysis
Training
Visualization
Geoscience and remote sensing
Feature extraction
Radar polarimetry
Marine vehicles
Synthetic aperture radar
Synthetic aperture radar (SAR)
ship detection
saliency
attention
feature pyramid network (FPN)
- Language
- ISSN
- 2153-7003
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.