April 2, 2024, 7:50 p.m. | Siting Zhu, Renjie Qin, Guangming Wang, Jiuming Liu, Hesheng Wang

cs.CV updates on arXiv.org arxiv.org

arXiv:2403.07494v2 Announce Type: replace-cross
Abstract: We propose SemGauss-SLAM, the first semantic SLAM system utilizing 3D Gaussian representation, that enables accurate 3D semantic mapping, robust camera tracking, and high-quality rendering in real-time. In this system, we incorporate semantic feature embedding into 3D Gaussian representation, which effectively encodes semantic information within the spatial layout of the environment for precise semantic scene representation. Furthermore, we propose feature-level loss for updating 3D Gaussian representation, enabling higher-level guidance for 3D Gaussian optimization. In addition, to …

abstract arxiv cs.cv cs.ro embedding feature information mapping quality real-time rendering representation robust semantic slam spatial tracking type

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