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cgtuebingen / Flex-Convolution

Source code for: Flex-Convolution (Million-Scale Point-Cloud Learning Beyond Grid-Worlds), accepted at ACCV 2018
Apache License 2.0
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Efficient knn on large points sets #11

Closed QingyongHu closed 5 years ago

QingyongHu commented 5 years ago

Thanks for your code.

It seems that knn_bruteforce function only support point sets less than 8k. As the warning shows:

"point sets greater than 8k are not yet supported!! Change to knn_graph operation!! "

Is there any efficient way to perform knn on large point set? (e.g. when the number of points is 100K or even more), otherwise, I still have to split the scene as many blocks or sample a part of points from the whole scene each time. However, this will undoubtedly lose the geometry information.

PatWie commented 5 years ago

This is ongoing work we haven't published yet. Note, in the paper we had a static scene such that a simple kd-tree beforehand did the job.

But, we already have a new network-layer that can compute these neighborhoods on-the-fly for larger point-clouds. Stay tuned :-)

MacOS commented 5 years ago

Thank you for your work and publishing your code!

Note, in the paper we had a static scene such that a simple kd-tree beforehand did the job.

I'm curious, which implementation of kd-tree did you use?

But, we already have a new network-layer that can compute these neighborhoods on-the-fly for larger point-clouds. Stay tuned :-)

Can you give me any time frame within you plan to make this public?

Thank you in advance!