A Deployment-Oriented Real-Time Transformer Detector and Benchmark for Maritime Search and Rescue Under Severe Sea Clutter

Maritime search and rescue (SAR) is a time-critical public safety mission that increasingly relies on unmanned vehicles to localize persons overboard. However, reliable onboard perception is challenged by extreme scale variation and heavy sea clutter under strict latency and compute budgets. We present R-DET, a deployment-oriented end-to-end Transformer detector built on the RT-DETR paradigm, featuring three rescue-oriented designs: (i) a lightweight backbone (Rescue-Net) preserving multi-scale cues, (ii) a bounded-cost global-context module (Rescue Attention) suppressing sea clutter, and (iii) an efficient fusion module (Rescue-FPN) injecting high-resolution details for tiny targets. We further introduce MarineRescue-8K, a benchmark collected from real maritime operations with a mission-aligned ignore region protocol that reduces the influence of non-critical clutter during optimization and evaluation. On MarineRescue-8K, R-DET achieves 84.1% [email protected] with only 14.5 M parameters at 63.2 FPS (RTX 2080 SUPER), demonstrating a favorable accuracy–efficiency trade-off for deployment-oriented maritime SAR perception.