We introduce a novel large-scale scene reconstruction benchmark using the newly developed 3D representation approach, Gaussian Splatting, on our expansive U-Scene dataset. U-Scene encompasses over one and a half square kilometres, featuring a comprehensive RGB dataset coupled with LiDAR ground truth. For data acquisition, we employed the Matrix 300 drone equipped with the high-accuracy Zenmuse L1 LiDAR, enabling precise rooftop data collection. This dataset, offers a unique blend of urban and academic environments for advanced spatial analysis convers more than 1.5 km$^2$. Our evaluation of U-Scene with Gaussian Splatting includes a detailed analysis across various novel viewpoints. We also juxtapose these results with those derived from our accurate point cloud dataset, highlighting significant differences that underscore the importance of combine multi-modal information

翻译：我们提出了一种新颖的大规模场景重建基准，该基准采用最新发展的三维表示方法——高斯泼溅，在广泛的U-Scene数据集上进行评估。U-Scene覆盖超过1.5平方公里，包含综合的RGB数据集及激光雷达真值数据。数据采集采用配备高精度Zenmuse L1激光雷达的Matrix 300无人机，实现了精确的屋顶数据收集。该数据集融合了城市与学术环境的独特组合，覆盖面积超过1.5平方公里，支持高级空间分析。我们基于高斯泼溅对U-Scene的评估包括跨多种新颖视角的详细分析，并将结果与基于精确点云数据集的结果进行对比，揭示了多模态信息融合的重要性。