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

AquaBEV: Monocular Underwater BEV Occupancy with 3D Sonar Supervision

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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.

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