Semantic3D
Introduced by Hackel et al. in Semantic3D.net: A new Large-scale Point Cloud Classification Benchmark
Semantic3D is a point cloud dataset of scanned outdoor scenes with over 3 billion points. It contains 15 training and 15 test scenes annotated with 8 class labels. This large labelled 3D point cloud data set of natural covers a range of diverse urban scenes: churches, streets, railroad tracks, squares, villages, soccer fields, castles to name just a few. The point clouds provided are scanned statically with state-of-the-art equipment and contain very fine details.
Source: Tangent Convolutions for Dense Prediction in 3DBenchmarks
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