Weakly Supervised Video Anomaly Detection On
Metrics
AUC-ROC
Results
Performance results of various models on this benchmark
Model Name | AUC-ROC | Paper Title | Repository |
|---|---|---|---|
| OPVAD | 96.98 | - | - |
| S3R | 97.48 | Self-supervised Sparse Representation for Video Anomaly Detection | |
| CLAV-CoMo | 97.59 | Look Around for Anomalies: Weakly-Supervised Anomaly Detection via Context-Motion Relational Learning | - |
| MIL-Rank | 85.33 | Real-world Anomaly Detection in Surveillance Videos | - |
| DMU | 97.57 | - | - |
| OCC-WS | 96.33 | - | - |
| RTFM | 97.21 | Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning | - |
| BN-SVP | 96.00 | - | - |
| UML | 96.78 | - | - |
| MIST | 94.83 | MIST: Multiple Instance Self-Training Framework for Video Anomaly Detection | - |
| RTFM-BERT | 97.54 | - | - |
| STPrompt | 97.81 | Weakly Supervised Video Anomaly Detection and Localization with Spatio-Temporal Prompts | - |
| VadCLIP | 97.49 | - | - |
| AR-Net | 91.24 | Weakly Supervised Video Anomaly Detection via Center-guided Discriminative Learning | - |
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