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

About test set #10

Open
sseunghyuns opened this issue Apr 17, 2024 · 0 comments
Open

About test set #10

sseunghyuns opened this issue Apr 17, 2024 · 0 comments

Comments

@sseunghyuns
Copy link

Thanks for your great work.

I have some questions about Wild6D annotated test set.
I'm currently using my model trained on the NOCS dataset for evaluation, and I've encountered some concerns with the RT error results, particularly in the parts marked in red.
image

Upon visualizing the results with evaluate_wild6d.py, I noticed that several inference outcomes were significantly incorrect.
image

It turns out that the masks used to generate the point clouds were incorrectly annotated. Including such improperly annotated masks in the evaluation seems to have skewed the results.
image

Is there something I might have missed while loading the test data? (I'm currently using evaluate_wild6d.py to load the data, and load the depth map and mask with that code.)

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