开源的哨兵-1船舶检测数据集，助力海事监控研究。
OSSDD - a New Open Dataset for Sentinel-1 Ship Detection
- 基于OpenSARShip构建，含15,197幅Sentinel-1 SAR图像块
- 包含55,759艘船的二值掩码与旋转/轴对齐框标注
- 支持多种检测模型训练，适配遥感与海洋智能分析
合成孔径雷达（SAR）图像中的船舶检测对海上态势感知至关重要，尤其在打击非法捕捞、走私和越境等行为方面。当前基于神经网络的船舶检测方法通常需要大规模训练数据，而此类数据在SAR领域远少于光学领域。尽管已有若干免费数据集，但其可用性和实用性参差不齐。本文提出OpenSARShip-Ship Detection Dataset（OSSDD），基于知名OpenSARShip 1.0数据集构建，用于训练SAR船舶检测神经网络。OSSDD免费开放，包含15,197个Sentinel-1幅度图像块（VV与VH极化），以及55,759艘船的二值掩码、轴对齐边界框和旋转边界框标注。本文展示了数据集构建过程、数据结构及下载内容，并使用Faster R-CNN、FCOS、DETR三种常见检测模型进行实验，结果可作为未来研究的基准。数据集已发布于Hugging Face：https://huggingface.co/datasets/sylviaHoch/OpenSARShip-Ship-Detection-Dataset。
原文摘要 · Abstract (English)
Ship detection in Synthetic Aperture Radar (SAR) images plays an important role for maritime situational awareness, especially with respect to different illegal activities at sea such as illegal fishing, smuggling or border violations. Modern ship detection methods using neural networks usually require large training datasets, which are considerably scarcer in the SAR domain than in the electro-optical domain. While several free datasets exist for this task, their availability and usability vary. In this paper, OpenSARShip-Ship Detection Dataset (OSSDD), a new dataset based on the well-known OpenSARShip 1.0 dataset is proposed for training neural networks for SAR ship detection. OSSDD is freely available and contains 15,197 Sentinel-1 amplitude patches in VV and VH polarization, binary ship masks, axis-aligned bounding box and rotated bounding box annotations for a total of 55,759 ships. The construction of the dataset, the contents and structure of the downloadable data and experiments with three common detector models (Faster R-CNN, FCOS, DETR) are shown and discussed. The results serve as benchmarks for future experiments. The dataset is available on Hugging Face at https://huggingface.co/datasets/sylviaHoch/OpenSARShip-Ship-Detection-Dataset.
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