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

base and novel classes #21

Open
Nathan-Li123 opened this issue Aug 23, 2024 · 1 comment
Open

base and novel classes #21

Nathan-Li123 opened this issue Aug 23, 2024 · 1 comment

Comments

@Nathan-Li123
Copy link

The 1,203 categories in LVIS are divided into 866 base categories and 337 novel categories. However, in the training set of the TAO dataset, there are actually only 208 base categories. Does this mean that it is not feasible to train using only the TAO dataset?

@siyuanliii
Copy link
Collaborator

Thanks for the question. We also include images from the LVIS dataset for training. For example, we will use LVIS base classes to train the open-vocabulary detector, then we only using the TAO training set to train the tracking part as in the paper TET. However, as you may note, the TAO training set is very small and insufficient. In the OVTrack, we give up the TAO training set and use the diffusion model to generate training data from LVIS images.

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