SOVIS

A Sonar-Visual Dataset for Cross-Modal Underwater Robot Perception

arXiv:2606.01398v1 Announce Type: new Abstract: Underwater robots typically use both cameras and sonar for perception to leverage the rich semantic details of vision and the robust range measurements of acoustics. However, learning to map between these modalities via cross-modal prediction remains underexplored due to limited sonar-visual paired datasets. We present SOVIS, a sonar-visual dataset for cross-modal underwater perception.