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Just a handful of annotated examples can dramatically close the performance gap between zero-shot and fully supervised open-vocabulary segmentation.
By learning to prioritize edges based on global consistency, this method constructs more reliable and compact pose graphs for Structure-from-Motion, outperforming traditional nearest neighbor retrieval, especially in ambiguous scenes.