EdwardSmith1884 / GEOMetrics

Repo for the paper "GEOMetrics: Exploiting Geometric Structure for Graph-Encoded Objects"
MIT License
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Where is the code of adaptive face splitting? #11

Closed Zhangsihao-Yang closed 4 years ago

Zhangsihao-Yang commented 4 years ago

I did not see the code that does the adaptive face splitting in GEOMetric.py. Could you guide me to the position?

Zhangsihao-Yang commented 4 years ago

I could see that part of the code in the old_GEOMetrics folder. But should it be used in the new folder?

EdwardSmith1884 commented 4 years ago

No, I leave it out in the interest of large speed ups from vectorization.

KnightOfTheMoonlight commented 4 years ago

Could you make it public? @EdwardSmith1884. It looks like you treat the face split part as an end-to-end learning part for your whole project. However, after the face split, the adjacency matrix should be updated. If it is a post-process part, then It has no effect at all, cause this part will have not affect to the mesh deformation part.

EdwardSmith1884 commented 4 years ago

@KnightOfTheMoonlight the code is public already here. Face splitting is not a post-processing step. It happens during learning. Quite a bit of work was put into making the adjacency matrix update somewhat efficient.

KnightOfTheMoonlight commented 4 years ago

@EdwardSmith1884 as your updated code does not contain the face slit part, your updated results from this comment https://github.com/EdwardSmith1884/GEOMetrics/issues/1#issuecomment-593428137 are obtained from no face split part too?

EdwardSmith1884 commented 4 years ago

Yes this is with no space splitting.

KnightOfTheMoonlight commented 4 years ago

@EdwardSmith1884 Then this is against your ablation study part in your paper. Table 2. You have proven face split has improved the performance from 50.33 to 56.61 for the chair category.

EdwardSmith1884 commented 4 years ago

No, this improvement is from:

The face splitting was removed so that I could vectorize the training process, and make it as fast as possible.