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Interactive 3D simulations have enabled breakthroughs in robotics andcomputer vision, but simulating the broad diversity of environments needed fordeep learning requires large corpora of photo-realistic 3D object models. Toaddress this need, we present Google Scanned Objects, an open-source collectionof over one thousand 3D-scanned household items released under a CreativeCommons license; these models are preprocessed for use in Ignition Gazebo andthe Bullet simulation platforms, but are easily adaptable to other simulators.We describe our object scanning and curation pipeline, then provide statisticsabout the contents of the dataset and its usage. We hope that the diversity,quality, and flexibility of Google Scanned Objects will lead to advances ininteractive simulation, synthetic perception, and robotic learning.

Google Scanned Objects: A High-Quality Dataset of 3D Scanned Household Items