8000 GitHub - AnasEmad11/C2FPL: A Coarse-to-Fine Pseudo-Labeling (C2FPL) Framework for Unsupervised Video Anomaly Detection
[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
Skip to content

AnasEmad11/C2FPL

Repository files navigation

C2FPL

A Coarse-to-Fine Pseudo-Labeling (C2FPL) Framework for Unsupervised Video Anomaly Detection (WACV 2024)

Training

Setup

Please download the concatenated extracted I3d features for XD-Violence and UCF-Crime dataset from links below:

The following files need to be adapted in order to run the code on your own machine:

  • Change the file paths to the downloaded features above in concatenated/concat_UCF.npy and concatenated/Concat_test_10.npy.
  • Feel free to change the hyperparameters in option.py

Train and test

After the setup, simply run the following commands:

sh train.sh
sh test.sh

About

A Coarse-to-Fine Pseudo-Labeling (C2FPL) Framework for Unsupervised Video Anomaly Detection

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published
0