GauU-Scene: A Scene Reconstruction Benchmark on Large Scale 3D
Reconstruction Dataset Using Gaussian Splatting
- URL: http://arxiv.org/abs/2401.14032v1
- Date: Thu, 25 Jan 2024 09:22:32 GMT
- Title: GauU-Scene: A Scene Reconstruction Benchmark on Large Scale 3D
Reconstruction Dataset Using Gaussian Splatting
- Authors: Butian Xiong, Zhuo Li, Zhen Li
- Abstract summary: We introduce a novel large-scale scene reconstruction benchmark using the newly developed 3D representation approach, Gaussian Splatting.
U-Scene encompasses over one and a half square kilometres, featuring a comprehensive RGB dataset and LiDAR ground truth.
This dataset, offers a unique blend of urban and academic environments for advanced spatial analysis.
- Score: 5.968501319323899
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: 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
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