A geometry-consistent pre-training paradigm using masked inlier reconstruction and a dual-stream encoder produces more robust and generalizable correspondence pruning for camera pose estimation and related 3D tasks.
Distinctive image features from scale-invariant keypoints.International Journal of Computer Vision, 60(2):91–110
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Scalable and Generalizable Correspondence Pruning via Geometry-Consistent Pre-training
A geometry-consistent pre-training paradigm using masked inlier reconstruction and a dual-stream encoder produces more robust and generalizable correspondence pruning for camera pose estimation and related 3D tasks.