×VerfasserIn
	0000-0002-3436-4879
	University of Rostock, Institute of Computer Science

Muhammad Salman Shaukat

Synthetic MBES Dataset for Underwater 3D Object Detection : [research data]

University of Rostock, 2026

https://doi.org/10.18453/rosdok_id00005050

Abstract: This dataset contains 100 synthetically generated multi-beam echosounder (MBES) 3D point clouds for the development and evaluation of underwater 3D object detection methods. The simulated environments were inspired by the artificial reef at the Digital Ocean Lab (DOL) near Nienhagen, Germany, and consist of procedurally generated seabeds populated with four types of artificial reef structures: small tetrapods, large tetrapods, reef cones, and concrete rings. The dataset contains a total of 5,491 annotated object instances. Each point cloud is accompanied by ground-truth 3D bounding-box annotations specifying the object class, dimensions, position, and orientation. The dataset was generated using a physics-based simulation pipeline and is intended to support research on 3D object detection from sonar point clouds, particularly in scenarios where annotated real-world sonar data are scarce.

data publication   free access