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Current event-based SLAM algorithms falter when faced with the full complexity of high-speed, 6-DoF maneuvers, highlighting a gap between current capabilities and the promise of event cameras.
Fusing semantic and geometric cues yields more robust and discriminative local features, outperforming methods relying on single appearance cues.
