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

Questions about offsets #69

Open
wWHWw opened this issue Nov 8, 2020 · 3 comments
Open

Questions about offsets #69

wWHWw opened this issue Nov 8, 2020 · 3 comments

Comments

@wWHWw
Copy link

wWHWw commented Nov 8, 2020

Hi ! Excellent work on making this implementation of Deformable Convolution.

When I used DCN to replace some of my backbone conv to train an network for object tracking problem, I found that simply replaced the conv to DCN didn't improve performance as expect and it decreased for about 6-8% on both precession and succese.
When I check the offset value during training, offset mean can reach about 100 or even larger.And the responds feature were much more ambiguous than normal convolution.

So is there any solutions to fix or contain the offsets during learning, so the receptive field can be limited to a fixed area?

@YiRuChenbilibili
Copy link

你好,在可变形卷积的使用上我遇到了同样的问题。请问你最后怎么修改的?或者只是单纯地不使用了?

@wWHWw
Copy link
Author

wWHWw commented Apr 12, 2022

你好,在可变形卷积的使用上我遇到了同样的问题。请问你最后怎么修改的?或者只是单纯地不使用了?

不太记得了,印象里是没查出为什么

@YiRuChenbilibili
Copy link

YiRuChenbilibili commented Apr 12, 2022 via email

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