-
Notifications
You must be signed in to change notification settings - Fork 76
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
After obtaining the final temporal feature representation X #39
Comments
Hi,
|
Hard normal will be the snippets that are similar to abnormal events. Pseudo abnormal means there may be snippets that are not actual abnormal because we try to select abnormal instances from the abnormal bag. There are no snippet-level labels. I don't quite understand your second question. Sorry.. |
Thank you so much @tianyu0207, I hope you will reply! |
each batch has the same number of normal and abnormal videos does not necessarily mean you have the equal number of videos in the dataset. you just sample evenly for each batch. Hi I reckon Your figure is correct. |
Thanks for viewing my issue, @tianyu0207
I have 4 questions that I hope you can explain:
The text was updated successfully, but these errors were encountered: