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

TokenCut false positives when there is no object in the image #20

Open
surajbijjahalli opened this issue Jun 18, 2023 · 2 comments
Open

Comments

@surajbijjahalli
Copy link

Im trying to apply TokenCut to a dataset in which there is a combination of images without salient objects (flat, relatively textureless images), and images in which there are clear objects (objects we are interested in). Is there a way of reducing false positives or some metric to indicate that the foreground segment is a weak one? or will TokenCut always return a segmentation even when there is no clear object in the scene ?

@XiSHEN0220
Copy link
Collaborator

Hi, nice question!

Currently, we don't have any strategies to filter the false positives samples.
I do think it would be a very good research direction.

Best,

Xi

@surajbijjahalli
Copy link
Author

Thank you Xi. Will post here when I find a good strategy !

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