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Point-supervised change detection can achieve performance on par with fully supervised methods by effectively refining noisy pseudo-labels through a novel two-stage optimization process.
Stop segmenting remote sensing images in isolation: modeling inter-unit dependencies boosts open-vocabulary segmentation accuracy by up to 6%.
