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

April 25, 2022 ยท Declared Dead ยท ๐Ÿ› IEEE International Conference on Robotics and Automation

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Authors Laura Downs, Anthony Francis, Nate Koenig, Brandon Kinman, Ryan Hickman, Krista Reymann, Thomas B. McHugh, Vincent Vanhoucke arXiv ID 2204.11918 Category cs.RO: Robotics Cross-listed cs.GR Citations 661 Venue IEEE International Conference on Robotics and Automation Last Checked 1 month ago
Abstract
Interactive 3D simulations have enabled breakthroughs in robotics and computer vision, but simulating the broad diversity of environments needed for deep learning requires large corpora of photo-realistic 3D object models. To address this need, we present Google Scanned Objects, an open-source collection of over one thousand 3D-scanned household items released under a Creative Commons license; these models are preprocessed for use in Ignition Gazebo and the Bullet simulation platforms, but are easily adaptable to other simulators. We describe our object scanning and curation pipeline, then provide statistics about the contents of the dataset and its usage. We hope that the diversity, quality, and flexibility of Google Scanned Objects will lead to advances in interactive simulation, synthetic perception, and robotic learning.
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