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

some questions about features extraction #14

Open
VV0808 opened this issue Jan 11, 2022 · 0 comments
Open

some questions about features extraction #14

VV0808 opened this issue Jan 11, 2022 · 0 comments

Comments

@VV0808
Copy link

VV0808 commented Jan 11, 2022

Thanks for the implementation of the paper.

I still have some questions about reproducing your result.

I use https://github.com/MILVLG/bottom-up-attention.pytorch to extract features, download r101'weight file(bua-caffe-frcn-r101_with_attributes.pth), and save the feature map from ’res4‘.(nms=0.3, score_thresh=0.1, min_bbox_num=10 and max_bbox_num=100)

All the feature maps are around 100G. However, you mentioned that your feature maps are around 300G in other issue.

I consider that i may make a mistake in features extraction so that i can't reproduce your result in the paper.

Can you check my method above?Thank you!

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