SensatUrban: Learning Semantics from Urban-Scale Photogrammetric Point Clouds

@article{Hu2022SensatUrbanLS,
  title={SensatUrban: Learning Semantics from Urban-Scale Photogrammetric Point Clouds},
  author={Qingyong Hu and Bo Yang and Sheikh Khalid and Wen Xiao and Niki Trigoni and A. Markham},
  journal={International Journal of Computer Vision},
  year={2022},
  pages={1-28}
}
  • Qingyong HuBo Yang A. Markham
  • Published 4 January 2022
  • Computer Science, Environmental Science
  • International Journal of Computer Vision
With the recent availability and affordability of commercial depth sensors and 3D scanners, an increasing number of 3D (i.e., RGBD, point cloud) datasets have been publicized to facilitate research in 3D computer vision. However, existing datasets either cover relatively small areas or have limited semantic annotations. Fine-grained understanding of urban-scale 3D scenes is still in its infancy. In this paper, we introduce SensatUrban, an urban-scale UAV photogrammetry point cloud dataset… 
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22 Citations
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