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Models/MPED-RNN

MPED-RNN

Reported on 13 benchmarks across 5 tasks · 2 papers · 10 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Computer Vision8 results

3D Anomaly DetectiononHR-ShanghaiTech
AUC· 2019-03-08
75.4
best: 87.23 (PoseWatch-H)
SOTA
Learning Regularity in Skeleton Trajectories for Anomaly Detection in Videos arXiv:1903.03295
3D Anomaly DetectiononHR-Avenue
AUC· 2019-03-08
86.3
best: 89.4 (TrajREC)
SOTA
Learning Regularity in Skeleton Trajectories for Anomaly Detection in Videos arXiv:1903.03295
3D Anomaly DetectiononHR-UBnormal
AUC· 2019-03-08
61.2
best: 68.4 (MoCoDAD)
SOTA
Learning Regularity in Skeleton Trajectories for Anomaly Detection in Videos arXiv:1903.03295
Video Anomaly DetectiononHR-ShanghaiTech
AUC· 2019-03-08
75.4
best: 87.23 (PoseWatch-H)
SOTA
Learning Regularity in Skeleton Trajectories for Anomaly Detection in Videos arXiv:1903.03295
Video Anomaly DetectiononHR-Avenue
AUC· 2019-03-08
86.3
best: 89.4 (TrajREC)
SOTA
Learning Regularity in Skeleton Trajectories for Anomaly Detection in Videos arXiv:1903.03295
Video Anomaly DetectiononHR-UBnormal
AUC· 2019-03-08
61.2
best: 68.4 (MoCoDAD)
SOTA
Learning Regularity in Skeleton Trajectories for Anomaly Detection in Videos arXiv:1903.03295
Video UnderstandingonVFP290K
ROC AUC
69.34
best: 96.02 (MPED-RNN (with memory extension))
VideoonVFP290K
ROC AUC
69.34
best: 96.02 (MPED-RNN (with memory extension))

Methodology5 results

Anomaly DetectiononPHEVA
AUC-ROC· 2024-08-26
76.05
SOTA
PHEVA: A Privacy-preserving Human-centric Video Anomaly Detection Dataset arXiv:2408.14329
Anomaly DetectiononHR-ShanghaiTech
AUC· 2019-03-08
75.4
best: 87.23 (PoseWatch-H)
SOTA
Learning Regularity in Skeleton Trajectories for Anomaly Detection in Videos arXiv:1903.03295
Anomaly DetectiononHR-Avenue
AUC· 2019-03-08
86.3
best: 89.4 (TrajREC)
SOTA
Learning Regularity in Skeleton Trajectories for Anomaly Detection in Videos arXiv:1903.03295
Anomaly DetectiononHR-UBnormal
AUC· 2019-03-08
61.2
best: 68.4 (MoCoDAD)
SOTA
Learning Regularity in Skeleton Trajectories for Anomaly Detection in Videos arXiv:1903.03295
Anomaly DetectiononVFP290K
ROC AUC
69.34
best: 96.02 (MPED-RNN (with memory extension))