Abnormal Event Detection In Video On Ucsd
Metrics
AUC
Results
Performance results of various models on this benchmark
Model Name | AUC | Paper Title | Repository |
|---|---|---|---|
| Background-Agnostic Framework | 98.7% | A Background-Agnostic Framework with Adversarial Training for Abnormal Event Detection in Video | |
| SSMTL | 97.5% | Anomaly Detection in Video via Self-Supervised and Multi-Task Learning | |
| AI-VAD | 99.1 | An Attribute-based Method for Video Anomaly Detection | |
| Adversarial Generator | 97.4% | Abnormal Event Detection in Videos using Generative Adversarial Nets | - |
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