Summary of Gauu-scene: a Scene Reconstruction Benchmark on Large Scale 3d Reconstruction Dataset Using Gaussian Splatting, by Butian Xiong et al.
GauU-Scene: A Scene Reconstruction Benchmark on Large Scale 3D Reconstruction Dataset Using Gaussian Splatting
by Butian Xiong, Zhuo Li, Zhen Li
First submitted to arxiv on: 25 Jan 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A newly developed 3D representation approach called Gaussian Splatting is used to create a large-scale scene reconstruction benchmark on the U-Scene dataset. This dataset features over one and a half square kilometers of RGB data, coupled with LiDAR ground truth, providing a comprehensive platform for advanced spatial analysis. The dataset was acquired using a Matrix 300 drone equipped with a high-accuracy Zenmuse L1 LiDAR, enabling precise rooftop data collection. The U-Scene dataset offers a unique blend of urban and academic environments, making it an ideal benchmark for testing scene reconstruction models. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary A team of researchers has created a big database that helps computers learn how to make maps. They used a special camera-equipped drone to take lots of pictures and gather information about the world. This database is called U-Scene and it’s really big, covering over 1.5 square kilometers! It includes pictures from both urban (city) and academic (school) environments. The researchers are using this database to test how well computers can make maps by comparing their results with a different type of data. |
