BuildingNet

Introduced by Selvaraju et al. in BuildingNet: Learning to Label 3D Buildings

BuildingNet is a large-scale dataset of 3D building models whose exteriors are consistently labeled. The dataset consists on 513K annotated mesh primitives, grouped into 292K semantic part components across 2K building models. The dataset covers several building categories, such as houses, churches, skyscrapers, town halls, libraries, and castles.

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