提案されたSemGauss-SLAMは、3Dガウス表現を活用した最初のセマンティックSLAMシステムであり、正確なセマンティックマッピングと写実的な再構築を実現します。
Neural implicit representation enhances semantic mapping accuracy and real-time tracking in SNI-SLAM.
Our SNI-SLAM leverages multi-modal features to conduct semantic SLAM based on Neural Radiance Fields, achieving higher accuracy and real-time semantic mapping. The approach involves feature collaboration between appearance, geometry, and semantics for enhanced representation capabilities.