Video Anomaly Detection On Hr Avenue
Metrics
AUC
Results
Performance results of various models on this benchmark
Model Name | AUC | Paper Title | Repository |
|---|---|---|---|
| BiPOCO | 87.0 | BiPOCO: Bi-Directional Trajectory Prediction with Pose Constraints for Pedestrian Anomaly Detection | - |
| Multi-timescale Prediction | 88.33 | Multi-timescale Trajectory Prediction for Abnormal Human Activity Detection | - |
| Conv-AE | 84.8 | Learning Temporal Regularity in Video Sequences | - |
| MoCoDAD | 89.0 | Multimodal Motion Conditioned Diffusion Model for Skeleton-based Video Anomaly Detection | - |
| COSKAD-euclidean | 87.8 | Contracting Skeletal Kinematics for Human-Related Video Anomaly Detection | - |
| COSKAD-radial | 82.2 | Contracting Skeletal Kinematics for Human-Related Video Anomaly Detection | - |
| GEPC | 58.1 | Graph Embedded Pose Clustering for Anomaly Detection | - |
| MPED-RNN | 86.3 | Learning Regularity in Skeleton Trajectories for Anomaly Detection in Videos | - |
| COSKAD-hyperbolic | 87.3 | Contracting Skeletal Kinematics for Human-Related Video Anomaly Detection | - |
| TrajREC | 89.4 | Holistic Representation Learning for Multitask Trajectory Anomaly Detection | - |
| Pred | 86.2 | Future Frame Prediction for Anomaly Detection -- A New Baseline | - |
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