arXiv Computer Vision
Sep 7

AquaBEV: Monocular Underwater BEV Occupancy with 3D Sonar Supervision

AquaBEV is a monocular underwater occupancy model that predicts local bird’s‑eye‑view (BEV) occupancy from a single RGB image. It uses paired 3D imaging sonar data as geometric supervision during training, mapping visual features into a calibration‑free polar representation and decoding along the range dimension before reconstructing Cartesian BEV coordinates. In a controlled underwater occupancy benchmark, AquaBEV outperforms the strongest transferred baseline with 31.4 % Visible IoU and 38.6 % Observed IoU, achieving 4.0 % and 4.3 % relative improvements respectively.

By Trung Tien Dong, Shengji Jin, Chen Chen, Yi Sheng, Xiaomin Lin
arXiv Computer Vision
Sep 1

Calibration and Comparative Analysis of Forward-Looking Sonar and 3D Sonar for Enhanced Underwater Object Recognition

arXiv:2608.29433v1 Announce Type: new Abstract: Sonars generate a significant amount of noise. With the advent of new technology capable of producing full 3D point clouds, the noise is amplified in s...

By Aditya Penumarti, Khanh Dong, Zi-Hao Zhang, Yongkyoon Park, Zhenqi Wu, Trung Dong, Shahriar Negahdaripour, Xiaomin Lin, Jane Shin
arXiv Machine Learning
Aug 3

ASVSim (AirSim for Surface Vehicles): A High-Fidelity Simulation Framework for Autonomous Surface Vehicle Research

arXiv:2506. 22174v3 Announce Type: replace-cross Abstract: The transport industry has recently shown significant interest in unmanned surface vehicles (USVs), specifically for port and inland waterway transport.

By Bavo Lesy, Siemen Herremans, Robin Kerstens, Jan Steckel, Walter Daems, Siegfried Mercelis, Ali Anwar