An ensemble of hyperspectral CLIP/DINO models and four-season RGB GeoRSCLIP embeddings, enriched with location and regression metadata text and compressed via SVD, won the Embed2Scale challenge.
Learning transferable visual models from natural language supervision
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Geospatial Foundational Embedder: Top-1 Winning Solution on EarthVision Embed2Scale Challenge (CVPR 2025)
An ensemble of hyperspectral CLIP/DINO models and four-season RGB GeoRSCLIP embeddings, enriched with location and regression metadata text and compressed via SVD, won the Embed2Scale challenge.