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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.
By combining SAM's segmentation prowess with homography estimation, these new planar trackers leapfrog existing methods by a significant margin, setting a new state-of-the-art on standard benchmarks.
