Toronto-3D

홈페이지 · 논문 24편

Toronto-3D is a large-scale urban outdoor point cloud dataset acquired by an MLS system in Toronto, Canada for semantic segmentation. This dataset covers approximately 1 km of road and consists of about 78.3 million points. Point clouds has 10 attributes and classified in 8 labelled object classes. Source: https://github.com/WeikaiTan/Toronto-3D Image Source: https://github.com/WeikaiTan/Toronto-3D

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