Skip to content
/ CU-Net Public

[CVPR 2023] Official code for paper: Exploiting Completeness and Uncertainty of Pseudo Labels for Weakly Supervised Video Anomaly Detection

Notifications You must be signed in to change notification settings

ArielZc/CU-Net

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

7 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

CU-Net

[CVPR 2023] Official code for paper: Exploiting Completeness and Uncertainty of Pseudo Labels for Weakly Supervised Video Anomaly Detection

The features used in the project are from this repo.

Testing

Pretrained models

Download the pretrained models, then run the following command:

python testing/stage2_test.py

About

[CVPR 2023] Official code for paper: Exploiting Completeness and Uncertainty of Pseudo Labels for Weakly Supervised Video Anomaly Detection

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages