Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

PCN inference and test #9

Open
stefano-mazz opened this issue Apr 12, 2022 · 1 comment
Open

PCN inference and test #9

stefano-mazz opened this issue Apr 12, 2022 · 1 comment

Comments

@stefano-mazz
Copy link

Hi, i do not understand how is generated a 16384 point cloud in output during the inference. The input point cloud is repeated 8 times and then fed into the network as [8, 2048,3] and then obtaining 8 different outputs they are reshaped to obtain a 16384 point cloud, if i have understood correctly. By running the line partial = random_subsample(partial.repeat((1, 8, 1)).reshape(-1, 16384, 3)) i get a partial point cloud of size [1,2048,3] instead of [b*8, 2048,3]. So, the output of the network is still 2048. Can you give me further explanation about this?
Thank you in advance.

@AllenXiangX
Copy link
Collaborator

@stefano-mazz The shape of the input point cloud is [b, 16384, 3], so after "partial.repeat((1, 8, 1)).reshape(-1, 16384, 3))", the shape is [b8, 16384, 3], and after the random_subsample, if becomes [b8, 2048, 3].

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants