SAMST refines pseudo-labels with SAM prompts derived from connected regions and threshold filtering, improving semi-supervised remote sensing segmentation on Potsdam at 1/32 labeled data.
Classhyper: Classmix-based hybrid perturbations for deep semi-supervised semantic segmentation of remote sensing imagery,
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SAMST: A Transformer framework based on SAM pseudo label filtering for remote sensing semi-supervised semantic segmentation
SAMST refines pseudo-labels with SAM prompts derived from connected regions and threshold filtering, improving semi-supervised remote sensing segmentation on Potsdam at 1/32 labeled data.