Data Set ScanNet

Published on April 27th, 2017 | by

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Publishing 3D Data to Benefit Indoor Robotics

Researchers from Stanford University, Princeton University, and the Technical University of Munich have published a new dataset called ScanNet consisting of 3D scans of 1,513 indoor environments, which include millions of annotations of household objects, that can serve as valuable training data for robotics developers as they work to improve the object recognition and navigation of indoor robots. The researchers used 3D cameras and took pictures from 2.5 million camera angles to make the scans, and then used Amazon’s Mechanical Turk crowdsourcing platform to annotate their contents.

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