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

Architecture dimension #35

Open
hailuu684 opened this issue Apr 1, 2023 · 0 comments
Open

Architecture dimension #35

hailuu684 opened this issue Apr 1, 2023 · 0 comments

Comments

@hailuu684
Copy link

Hello everyone,
I would like to ask about the varifocalNet head architecture. As I understand, the output from feature pyramid has different levels and thus different dimensions. However, I read in the paper, you shown that the input dimension to the head is HxWx256. Is it the same for every levels? The outputs from feature pyramid with backbone resnet50 are (batch, 256, 52, 52), (batch, 256, 26, 26), (batch, 256, 13, 13), (batch, 256, 7, 7), (batch, 256, 4, 4) which mean that I need to upsample to HxW for every feature height and width?
I hope my question will get a reply :D. Have a good day and research.

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