Synthetic MBES Dataset for Underwater 3D Object Detection: [research data] Shaukat, Muhammad Salman (VerfasserIn) Computerdaten Forschungsdaten 2026 2026 eng electronicelectronic resourceremoteComputermedienOnline-Ressource1 Online-Ressource 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. Open Access Namensnennung 4.0 International M. Salman Shaukat This research was supported by the BMBF, OTC-Digital Twin & Analytics (OTC-DaTA) project (03ZU1107FB) 004 http://purl.uni-rostock.de/rosdok/id00005050 10.1109/JOE.2026.3675841 doi: 10.18453/rosdok_id00005050 oclc: 1613390107 ppn: (DE-627)1982579714