Strong generalist vision foundation models match or outperform electro-optical specific models in remote sensing retrieval with better cross-scene stability.
Scale-mae: A scale-aware masked autoencoder for multiscale geospatial representation learning
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Rethinking Electro-Optical Vision Foundation Models for Remote Sensing Retrieval: A Controlled Comparison with Generalist VFM
Strong generalist vision foundation models match or outperform electro-optical specific models in remote sensing retrieval with better cross-scene stability.