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cs.CV2026
GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation
Gaetano Chiriaco, Luca Barco, Andrea Bragagnolo +2
Geospatial foundation models aim to learn representations that transfer across regions and sensors, yet evaluating them on specific tasks requires large, high-quality, multi-modal…
cs.CV2024
FMARS: Annotating Remote Sensing Images for Disaster Management using Foundation Models
Edoardo Arnaudo, Jacopo Lungo Vaschetti, Lorenzo Innocenti +4
Very-High Resolution (VHR) remote sensing imagery is increasingly accessible, but often lacks annotations for effective machine learning applications. Recent foundation models like…