APSAM converts image-level landslide labels into SAM box and point prompts derived from class activation maps, yielding pseudo-masks that beat prior weakly supervised methods on two landslide datasets.
A weakly super- vised semantic segmentation approach for damaged building extrac- tion from postearthquake high-resolution remote-sensing images,
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Auto-Prompting SAM for Weakly Supervised Landslide Extraction
APSAM converts image-level landslide labels into SAM box and point prompts derived from class activation maps, yielding pseudo-masks that beat prior weakly supervised methods on two landslide datasets.