Video Anomaly Detection On Ucsd Ped2 1
Metrics
AUC
Results
Performance results of various models on this benchmark
Model Name | AUC | Paper Title | Repository |
|---|---|---|---|
| AnomalyRuler | 97.9% | Follow the Rules: Reasoning for Video Anomaly Detection with Large Language Models | |
| MULDE-object-centric-micro | 99.7% | MULDE: Multiscale Log-Density Estimation via Denoising Score Matching for Video Anomaly Detection |
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