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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