AI RESEARCH
Lightweight SAR Ship Detection via Contrastive Distillation
arXiv CS.CV
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ArXi:2605.30380v1 Announce Type: new Deep convolutional and transformer-based detectors achieve strong performance for SAR ship detection but are often computationally prohibitive for real-time or onboard deployment. Lightweight models offer improved efficiency yet struggle to capture the complex structural relationships inherent in SAR backscatter. Most existing SAR knowledge-distillation approaches rely on feature or logit matching, which enforces localized activation similarity while neglecting the geometric relationships among object representations.