Google Scanned Objects: A High-Quality Dataset of 3D Scanned Household Items
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Cited by 133 in Diffusion models, but placed by its own abstract, which didn’t fit.
Abstract (arXiv)
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.
Key facts. Cited by 612 papers in the map (data through 14 Oct 2026). First posted on arXiv 25 Apr 2022.
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Citing papers per year: 2022: 20; 2023: 104; 2024: 198; 2025: 166; 2026: 124.
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