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Learning Which Correspondences to Trust: Confidence-Weighted Event-Camera Localization in LiDAR Maps
Localizing an event camera against a pre-built LiDAR map can be cast as dense optical-flow estimation between a rendered depth view and an event image, followed by a Perspective-n-Point (PnP) solver over the induced 3D-2D correspondences. Existing pipelines rely on geometric consensus during pose es
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