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

Which model ckpt to use for novel affordance detection of in-the-wild images #6

Open
tumble3eed opened this issue Jan 5, 2025 · 1 comment

Comments

@tumble3eed
Copy link

Thanks for your great work!
I am trying to use your model in my task and need to perform new affordance segmentation on in-the-wild object images.
I need a model that has seen more data and is more accurate. May I ask if your seen and unseen checkpoints were trained on the seen and unseen split of AGD20K, respectively? Which checkpoint should I use? Thank you!

@Reagan1311
Copy link
Owner

Hi, there. 1) For your specific task, you may need to re-annotate one-shot data, as the annotation standard of AGD20K might differ from what you need. 2) Yes, the seen and unseen checkpoints were trained on their respective splits of AGD20K. However, these checkpoints are not specifically tailored for novel affordance segmentation. Therefore, we recommend modifying the text prompt learning to train a new model as suggested in #5.

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