Comments (2)
Hey, thanks for your interest.
Could you please check if this can help?
#12 (comment)
For Fig. 10, we use dense sampling and virtual scanning to get surface points with normals. Once you get a dense point cloud with normals, you can effortlessly use any reconstruction methods (like Poisson) to recover a watertight surface.
If this can't help you figure it out, I will consider releasing a version of the implementation.
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Yes, this is very helpful. Commented code lines in the test.py was exactly what I needed.
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Related Issues (20)
- Which tool did you use to visualize qualitative results in your paper? HOT 2
- questions HOT 1
- Output Files HOT 4
- A new question about installing the Pointnet++ HOT 7
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- about using this method on complete and partial point cloud HOT 2
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- How to show/displace the testing result files? HOT 1
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