AI RESEARCH
Incremental Semantics-Aided Meshing from LiDAR-Inertial Odometry and RGB Direct Label Transfer
arXiv CS.CV
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ArXi:2604.09478v1 Announce Type: new Geometric high-fidelity mesh reconstruction from LiDAR-inertial scans remains challenging in large, complex indoor environments -- such as cultural buildings -- where point cloud sparsity, geometric drift, and fixed fusion parameters produce holes, over-smoothing, and spurious surfaces at structural boundaries. We propose a modular, incremental RGB+LiDAR pipeline that generates incremental semantics-aided high-quality meshes from indoor scans through scan frame-based direct label transfer.