AI RESEARCH
Transforming Omnidirectional RGB-LiDAR data into 3D Gaussian Splatting
arXiv CS.CV
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ArXi:2603.06061v1 Announce Type: new The demand for large-scale digital twins is rapidly growing in robotics and autonomous driving. However, constructing these environments with 3D Gaussian Splatting (3DGS) usually requires expensive, purpose-built data collection. Meanwhile, deployed platforms routinely collect extensive omnidirectional RGB and LiDAR logs, but a significant portion of these sensor data is directly discarded or strictly underutilized due to transmission constraints and the lack of scalable reuse pipeline.