arXiv Computer Vision
Geometric Coastline Localization using Vision-Language Models
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Jun 9
Geometric Coastline Localization using Vision-Language Models
Coastline detection in remote sensing imagery is commonly formulated as a pixel-wise segmentation problem, where the final coastline is extracted from a predicted mask through post-processing. This formulation relegates coastline geometry, the primary representation used in coastal change analysis, to a secondary artifact rather than the learning objective.
arXiv Computer Vision
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The Coastline as a Structural Constraint: Harnessing Scene Geometry for Autonomous Surface Vessel Localization
arXiv:2608.21276v1 Announce Type: cross Abstract: Coastal environments contain rich, largely unexploited geometric structure capable of providing globally referenced localization cues. In this work,...
arXiv Computer Vision
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Evaluation of Vision-Language Models Across Diverse Coastal Environments
The paper introduces a densely labeled coastal dataset of over 1,000 images from Oahu, Hawaii, featuring 18 semantic classes and 7,400 annotated instances. Seven modern vision‑language models were evaluated using text‑to‑mask, mask‑to‑mask, and mask‑to‑text alignment experiments. Results show that broad landscape classes are recognized more accurately than conventional object and coastal classes, with coastal concepts posing the greatest challenge; however, performance differences are not solely due to environmental context, and alternative textual labels improve recognition of several coastal concepts.
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arXiv Machine Learning
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CrevasseSeg: A Label-Efficient UAV Crevasse Segmentation Framework
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