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

我们引入了一种新颖的大规模场景重建基准测试，通过使用新开发的三维表示方法——高斯插值法在我们广泛的U-Scene数据集中。U-Scene包含了一个半平方千米以上的区域，具有综合RGB数据集和LiDAR地面真实数据。我们使用了Matrix 300无人机配备高精度的Zenmuse L1 LiDAR来获取数据，从而实现了精确的屋顶数据采集。这个数据集提供了一个独特的城市和学术环境的结合，用于高级空间分析，覆盖面积超过了1.5km^2。我们使用高斯插值法对U-Scene进行了评估，并从各种新颖的视角进行了详细分析。我们还将这些结果与我们准确的点云数据集进行对比，突出了多模态信息结合的重要性。

GauU-Scene: 使用高斯喷洒技术的大规模三维重构数据集上的场景重建基准测试