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

Using the Ground truth boxes as a history offline predictions in FSD++ #178

Open
rXYZkit opened this issue Jan 12, 2024 · 2 comments
Open

Comments

@rXYZkit
Copy link

rXYZkit commented Jan 12, 2024

Thank you very much for your work.

Have you tried using the Ground truth boxes as a history offline predictions versus using the predictions of a well-trained fsd model as a historical prediction even if you mention in your paper that the distribution gap between ground
truth used in training and predicted boxes.

@Abyssaledge
Copy link
Collaborator

No, I have not tried it. I believe there will be a performance gap if using the GT, which may not be very significant due to the well-trained FSD having high-quality predictions. Moreover, you can narrow the gap by randomly jittering the GT.

@rXYZkit
Copy link
Author

rXYZkit commented Jan 18, 2024

Thanks,

The predictions of a trained model will still contain FP and TN, which bboxes are not as accurate as gt produces for generating historical skeleton points when training. You mentioned using random jittering for gt, is that because less accurate skeleton points are more friendly to training?

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