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

what is the detail of limitations of second "dataset's distribution" #24

Open
justinday123 opened this issue May 8, 2023 · 3 comments

Comments

@justinday123
Copy link

what is the actual limitation?

@justinday123 justinday123 changed the title what is the detail of limitations of third "dataset's distribution" what is the detail of limitations of second "dataset's distribution" May 8, 2023
@dunbar12138
Copy link
Owner

Hi,

The limitation is that our model cannot generate out-of-distribution results, even if such input is given. Fig 16 in our arXiv paper is an example.

@justinday123
Copy link
Author

thanks. If there is no 'green cat' in dataset, than your model can't make '3d green cat?'. Or, your model trains about one class in one time?(ex: if your model trains about AFHQ, your model cannot generate about all the class in AFHQ in once?)
Also, the reason why your model cannot generate is because of EG3D?

Thank you for your comment

@dunbar12138
Copy link
Owner

If there is no 'green cat' in the training set, our model won't be able to generate it. Yes, I think it is a limitation for most of the GAN-based methods.

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