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

About the details of the code #4

Open
ideasplus opened this issue Dec 13, 2021 · 0 comments
Open

About the details of the code #4

ideasplus opened this issue Dec 13, 2021 · 0 comments

Comments

@ideasplus
Copy link

ideasplus commented Dec 13, 2021

Hello, thanks for your open-source code!

I want to know which part of the code is responsible for identifying occlusion and signal miss? I can't find it due to the complexity of this project. And can you give more explaination on the intution of identifying occlusion and signal miss in the spherical coordinate system? I can't understand it well.

Another question is about the process of model inference. Do we need to assemble the approximated complete shape for the test sample or just take the original sample as input and output the shape occupancy probablity?

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

1 participant