Small-sized unmanned surface vehicles (USV) are coastal water devices with a broad range of applications such as environmental control and surveillance. A crucial capability for autonomous operation is obstacle detection for timely reaction and collision avoidance, which has been recently explored in the context of camera-based visual scene interpretation. Owing to curated datasets, substantial advances in scene interpretation have been made in a related field of unmanned ground vehicles. However, the current maritime datasets do not adequately capture the complexity of real-world USV scenes and the evaluation protocols are not standardised, which makes cross-paper comparison of different methods difficult and hiders the progress. To address these issues, we introduce a new obstacle detection benchmark MODS, which considers two major perception tasks: maritime object detection and the more general maritime obstacle segmentation. We present a new diverse maritime evaluation dataset containing approximately 81k stereo images synchronized with an on-board IMU, with over 60k objects annotated. We propose a new obstacle segmentation performance evaluation protocol that reflects the detection accuracy in a way meaningful for practical USV navigation. Seventeen recent state-of-the-art object detection and obstacle segmentation methods are evaluated using the proposed protocol, creating a benchmark to facilitate development of the field.

中文翻译：

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MODS-面向USV的目标检测和障碍物分割基准

小型无人水面车辆（USV）是沿海水设备，具有广泛的应用，例如环境控制和监视。自主操作的一项关键功能是能够及时发现反应并避免碰撞的障碍物检测，近来在基于摄像机的视觉场景解释中已对此进行了探索。由于精选的数据集，无人地面车辆的相关领域在场景解释方面取得了重大进展。但是，当前的海事数据集无法充分反映现实世界中USV场景的复杂性，并且评估协议尚未标准化，这使得不同方法的跨纸张比较变得困难，并且无法实现。为了解决这些问题，我们引入了新的障碍物检测基准MODS，它考虑了两个主要的感知任务：海上物体检测和更一般的海上障碍物分割。我们提出了一个新的多样化海事评估数据集，其中包含与船载IMU同步的约81k立体图像，并标注了超过60k的对象。我们提出了一种新的障碍物分割性能评估协议，该协议以对实际USV导航有意义的方式反映了检测精度。使用提出的协议对17种最新的最新对象检测和障碍物分割方法进行了评估，从而为促进该领域的发展创造了基准。注释了超过6万个对象。我们提出了一种新的障碍物分割性能评估协议，该协议以对实际USV导航有意义的方式反映了检测精度。使用提出的协议对17种最新的最新对象检测和障碍物分割方法进行了评估，从而为促进该领域的发展创造了基准。注释了超过6万个对象。我们提出了一种新的障碍物分割性能评估协议，该协议以对实际USV导航有意义的方式反映了检测精度。使用提出的协议对17种最新的最新对象检测和障碍物分割方法进行了评估，从而为促进该领域的发展创造了基准。