Joint 2D-3D-Semantic Data for Indoor Scene Understanding

3 Feb 2017 Iro Armeni Sasha Sax Amir R. Zamir Silvio Savarese

We present a dataset of large-scale indoor spaces that provides a variety of mutually registered modalities from 2D, 2.5D and 3D domains, with instance-level semantic and geometric annotations. The dataset covers over 6,000m2 and contains over 70,000 RGB images, along with the corresponding depths, surface normals, semantic annotations, global XYZ images (all in forms of both regular and 360{\deg} equirectangular images) as well as camera information... (read more)

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2D-3D-S

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ImageNet SUN RGB-D SUNCG SUN3D SceneNN

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