arXiv AI
BenthicDINO: Physics-Informed Self-Distillation for View-Invariant Side-Scan Sonar Representations
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CoralBay: A Self-Supervised CT Foundation Model
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Weakly Supervised Seafloor Segmentation for Seagrass Habitat Mapping in Side-Scan Sonar Imagery
The paper presents a weakly supervised semantic segmentation approach for mapping seagrass habitats using side‑scan sonar imagery. By training a ViT‑based encoder‑decoder with image‑level labels, class activation maps are refined into pseudo‑labels and iteratively self‑trained, achieving high mean intersection‑over‑union scores (up to 89.3 %) without pixel‑level annotations. The method also benefits from self‑supervised pretraining and demonstrates generalizability in field trials.
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Physics-Guided Spatiotemporal Learning for Coastal Wave Peak Period Estimation from Video
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arXiv AI
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SonarLLM: A Native Sonar--Optical Multimodal Large Language Model for Underwater Perception
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arXiv AI
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Robust Cross-Modal Foundation Model Perception for Underwater Robots under Degraded Visual Conditions
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