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Rescan: Inductive Instance Segmentation for Indoor RGBD Scans
[article]
2019
arXiv
pre-print
In depth-sensing applications ranging from home robotics to AR/VR, it will be common to acquire 3D scans of interior spaces repeatedly at sparse time intervals (e.g., as part of regular daily use). We propose an algorithm that analyzes these "rescans" to infer a temporal model of a scene with semantic instance information. Our algorithm operates inductively by using the temporal model resulting from past observations to infer an instance segmentation of a new scan, which is then used to update
arXiv:1909.11268v1
fatcat:peg7makkunbhdkschsv5xwqvni