MapSR achieves 59.64% mIoU on land cover super-resolution from low-resolution labels alone by prompting frozen vision foundation models and applying training-free inference plus graph refinement.
A novel transformer based semantic segmentation scheme for fine-resolution remote sensing images,
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MapSR: Prompt-Driven Land Cover Map Super-Resolution via Vision Foundation Models
MapSR achieves 59.64% mIoU on land cover super-resolution from low-resolution labels alone by prompting frozen vision foundation models and applying training-free inference plus graph refinement.