Anomaly Detection In Surveillance Videos On 3
Metrics
AUC
Results
Performance results of various models on this benchmark
Model Name | AUC | Paper Title | Repository |
|---|---|---|---|
| SSMTL | 97.5 | Anomaly Detection in Video via Self-Supervised and Multi-Task Learning | - |
| CL-VAD | 97.8 | Continual Learning for Anomaly Detection in Surveillance Videos | - |
| Background-Agnostic Framework | 98.7 | A Background-Agnostic Framework with Adversarial Training for Abnormal Event Detection in Video | - |
| GCN-Anomaly | 93.2 | Graph Convolutional Label Noise Cleaner: Train a Plug-and-play Action Classifier for Anomaly Detection | - |
| FastAno | 96.3 | FastAno: Fast Anomaly Detection via Spatio-temporal Patch Transformation | - |
| RTFM | 98.6 | Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning | - |
0 of 6 row(s) selected.