MultiScan: Scalable RGBD scanning for 3D environments with articulated objects
Yongsen Mao, Yiming Zhang, Hanxiao Jiang, Angel X. Chang, Manolis Savva
Abstract
We introduce MultiScan, a scalable RGBD dataset construction pipeline leveraging commodity mobile devices to scan indoor scenes with articulated objects and web-based semantic annotation interfaces to efficiently annotate object and part semantics and part mobility parameters. We use this pipeline to collect 273 scans of 117 indoor scenes containing 10957 objects and 5129 parts. The resulting MultiScan dataset provides RGBD streams with per-frame camera poses, textured 3D surface meshes, richly annotated part-level and object-level semantic labels, and part mobility parameters. We validate our dataset on instance segmentation and part mobility estimation tasks and benchmark methods for these tasks from prior work. Our experiments show that part segmentation and mobility estimation in real 3D scenes remain challenging despite recent progress in 3D object segmentation.
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Install the CLIlune papers fulltext 8836b61e-bc4b-42d2-9a63-1c5a94b14e7aCited by top-tier papers31
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Builds on14
- 3D Scene Graph: A Structure for Unified Semantics, 3D Space, and CameraIro Armeni, Zhi-Yang He, Amir Zamir, JunYoung Gwak et al.ICCV 2019 · 474 citations
- RIO: 3D Object Instance Re-Localization in Changing Indoor EnvironmentsJohanna Wald, Armen Avetisyan, Nassir Navab, Federico Tombari et al.ICCV 2019 · 233 citations
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