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

Clarification about multi-bin classification loss? #43

Open
sauravshanu opened this issue Nov 11, 2021 · 1 comment
Open

Clarification about multi-bin classification loss? #43

sauravshanu opened this issue Nov 11, 2021 · 1 comment

Comments

@sauravshanu
Copy link

Hi,

Thanks for providing the code. I have a question about the multi-bin classification loss. In the Mono3D paper, it is mentioned that the cross-entropy loss is used for the multi-bin classification of width, height, and length.

However, looking at the code in detection_3d_head.py, I find that it is being used only for angle alpha. Am I understanding the code wrong? Can you please clarify that?

Thank you

@Owen-Liuyuxuan
Copy link
Owner

When I try to open-source the code, I made it easier to adapt to other datasets with more classes, so the multi-bin classification for rotation is skipped.

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