AI RESEARCH
DINO-Explorer: Active Underwater Discovery via Ego-Motion Compensated Semantic Predictive Coding
arXiv CS.CV
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ArXi:2604.12933v1 Announce Type: cross Marine ecosystem degradation necessitates continuous, scientifically selective underwater monitoring. However, most autonomous underwater vehicles (AUVs) operate as passive data loggers, capturing exhaustive video for offline review and frequently missing transient events of high scientific value. Transitioning to active perception requires a causal, online signal that highlights significant phenomena while suppressing maneuver-induced visual changes.