Detecting arbitrarily oriented ships in remote sensing images remains challenging due to diverse orientations, complex backgrounds, and scale variations, leading to a struggle in balancing detector accuracy with efficiency. We propose EfficientRDet, an enhanced rotated-ship detection algorithm built upon the EfficientDet framework. EfficientRDet adapts to rotated objects via an angle prediction branch and then significantly boosts accuracy with a novel pseudo-two-stage paradigm comprising a Rotated-Bounding-Box Refinement Branch (RRB) and a Class-Score Refinement Branch (CRB). Further precision is gained through an optimized Enhanced BiFPN (E-BiFPN), an Attention Head, and Distribution Focal (DF) angle representation. Extensive experiments on the HRSC2016 (optical) and RSDD-SAR datasets show that EfficientRDet consistently outperforms state-of-the-art methods, achieving 97.60% AP50 on HRSC2016 and 93.58% AP50 on RSDD-SAR. Comprehensive ablation studies confirm the effectiveness of all proposed mechanisms. EfficientRDet thus offers a promising and practical solution for precise, efficient ship detection across diverse remote sensing imagery.
Zuo et al. (Thu,) studied this question.