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Yes, non-keyframe point clouds lack labels, requiring the use of nearest neighbor methods to assign labels to unlabeled points, which can be a time-consuming task.
Thanks for your reply. Yes, it takes 96 CPU servers days. BTW, what’s the difference with CVPR 2023 occupancy GT ? Is that the same method to generate GT as yours?
Also, the recent OpenOccupancy repo releases it’s code as well for nuscenes. What’s the difference with your GT?
Thanks for your work.
But I find that it takes huge long time to generate trainval GT even with parallel generating. Also, it takes almost all CPU threads.
Is that same with your past practice?
Thanks!
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