Target Sampling Distribution

[kampelmuehler]

In the supplemental of the paper you state

To generate training point sets, we randomly sample
points on the ground-truth surface and displace them with
Gaussian distribution N (0, σ) along x, y and z axis, where
1% of points are sampled from σ = 0.08, 49% of points
from σ = 0.02 and 50% of points from σ = 0.003 as sug-
gested by [13]

, yet the data preparation you provide only takes a single sigma. Is this intentional?

EDIT: (answering my own question) The selection of samples according to the three different values of σ is taken care of during data loading - see https://github.com/zhaofang0627/AnchorUDF/blob/7df547fc89ac4c246300d6aba8a708e4b196d41b/lib/data/TrainDatasetDF3D.py#L228

I would suggest changing the README from

python -m apps.gen_targets --dataroot {path_of_dataset} --sigma {0.003, 0.02, or 0.08} --point_num 600

to at least

python -m apps.gen_targets --dataroot {path_of_dataset} --sigma {0.003, 0.02, AND 0.08} --point_num 600

to avoid confusion.

Maybe state that it needs to be run 3 times then.

[zhaofang0627]

Hi, thank you for your suggestion! I have updated the README to avoid confusion.

[kampelmuehler]

Thanks!