Web: http://arxiv.org/abs/2209.08263

Sept. 20, 2022, 1:12 a.m. | Thang Vu, Kookhoi Kim, Tung M. Luu, Thanh Nguyen, Junyeong Kim, Chang D. Yoo

cs.CV updates on arXiv.org arxiv.org

Existing state-of-the-art 3D point cloud instance segmentation methods rely
on a grouping-based approach that groups points to obtain object instances.
Despite improvement in producing accurate segmentation results, these methods
lack scalability and commonly require dividing large input into multiple parts.
To process a scene with millions of points, the existing fastest method
SoftGroup \cite{vu2022softgroup} requires tens of seconds, which is under
satisfaction. Our finding is that $k$-Nearest Neighbor ($k$-NN), which serves
as the prerequisite of grouping, is a computational bottleneck. …

arxiv scalable segmentation

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