ScanNet

by Angela Dai,Angel X. Chang,Manolis Savva,Maciej Halber,Thomas Funkhouser,Matthias NießnerUnknown

ScanNet

ScanNet is an RGB-D video dataset containing 2.5 million views in more than 1500 scans, annotated with 3D camera poses, surface reconstructions, and instance-level semantic segmentations. To collect this data, we designed an easy-to-use and scalable RGB-D capture system that includes automated surface reconstruction and crowdsourced semantic annotation. We show that using this data helps achieve state-of-the-art performance on several 3D scene understanding tasks, including 3D object classification, semantic voxel labeling, and CAD model retrieval.

Dataset Attributes

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Tasks3D Reconstruction
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CategoriesIndoor, Building, Architecture
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SensorRGB-D

Class Labels

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