GauU-Scene: A Scene Reconstruction Benchmark on Large Scale 3D
  Reconstruction Dataset Using Gaussian Splatting
Butian Xiong Zhuo Li Zhen Li
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