Real world Anomaly Detection in Surveillance Videos : Pytorch RE-Implementation
This repository is a re-implementation of "Real-world Anomaly Detection in Surveillance Videos" with pytorch. As a result of our re-implementation, we achieved a much higher AUC than the original implementation.
Download following data link and unzip under your $DATA_ROOT_DIR.
- Directory tree
DATA/ UCF-Crime/ ../all_rgbs ../~.npy ../all_flows ../~.npy train_anomaly.txt train_normal.txt test_anomaly.txt test_normal.txt
|Original paper(C3D two stream)||UCF-Crimes||75.41|
|RTFM (I3D RGB)||UCF-Crimes||84.03|
|Ours Re-implementation (I3D two stream)||UCF-Crimes||84.45|
This code is heavily borrowed from Learning to Adapt to Unseen Abnormal Activities under Weak Supervision and AnomalyDetectionCVPR2018.