SARES-DEIM: Sparse Mixture-of-Experts Meets DETR for Robust SAR Ship Detection

• URL: http://arxiv.org/abs/2604.04127v1
• Date: Sun, 05 Apr 2026 14:15:39 GMT
• Title: SARES-DEIM: Sparse Mixture-of-Experts Meets DETR for Robust SAR Ship Detection
• Abstract summary: Ship detection in Synthetic Aperture Radar (SAR) imagery is fundamentally challenged by inherent coherent speckle noise.<n>We propose SARES-DEIM, a domain-aware detection framework grounded in the DEtection TRansformer (DETR) paradigm.<n>Central to our approach is SARESMoE, a module leveraging a sparse gating mechanism to selectively route features toward specialized frequency and wavelet experts.
• Score: 13.697178700187402
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Ship detection in Synthetic Aperture Radar (SAR) imagery is fundamentally challenged by inherent coherent speckle noise, complex coastal clutter, and the prevalence of small-scale targets. Conventional detectors, primarily designed for optical imagery, often exhibit limited robustness against SAR-specific degradation and suffer from the loss of fine-grained ship signatures during spatial downsampling. To address these limitations, we propose SARES-DEIM, a domain-aware detection framework grounded in the DEtection TRansformer (DETR) paradigm. Central to our approach is SARESMoE (SAR-aware Expert Selection Mixture-of-Experts), a module leveraging a sparse gating mechanism to selectively route features toward specialized frequency and wavelet experts. This sparsely-activated architecture effectively filters speckle noise and semantic clutter while maintaining high computational efficiency. Furthermore, we introduce the Space-to-Depth Enhancement Pyramid (SDEP) neck to preserve high-resolution spatial cues from shallow stages, significantly improving the localization of small targets. Extensive experiments on two benchmark datasets demonstrate the superiority of SARES-DEIM. Notably, on the challenging HRSID dataset, our model achieves a mAP50:95 of 76.4% and a mAP50 of 93.8%, outperforming state-of-the-art YOLO-series and specialized SAR detectors.

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