-
Notifications
You must be signed in to change notification settings - Fork 22
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
Ablation study of auxiliary losses? #43
Comments
The intermediate loss splits the learning into multiple steps and may ease the learning process. I observed it improves both localization and captioning performance, but I didn't remember it helps convergence. The design follows the DETR and Deformable-DETR and you may find more analysis in these papers. |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Hello,
I was wondering about the role of auxiliary losses on each intermediate decoder layer. Can it help to accelerate the model convergence or for other purposes?
Thanks!
The text was updated successfully, but these errors were encountered: