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Models/GEPC

GEPC

Reported on 13 benchmarks across 5 tasks · 2 papers

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· 2019-12-26
74.8
best: 87.23 (PoseWatch-H)
Graph Embedded Pose Clustering for Anomaly Detection arXiv:1912.11850
3D Anomaly DetectiononHR-Avenue
AUC· 2019-12-26
58.1
best: 89.4 (TrajREC)
Graph Embedded Pose Clustering for Anomaly Detection arXiv:1912.11850
3D Anomaly DetectiononHR-UBnormal
AUC· 2019-12-26
55.2
best: 68.4 (MoCoDAD)
Graph Embedded Pose Clustering for Anomaly Detection arXiv:1912.11850
Video Anomaly DetectiononHR-ShanghaiTech
AUC· 2019-12-26
74.8
best: 87.23 (PoseWatch-H)
Graph Embedded Pose Clustering for Anomaly Detection arXiv:1912.11850
Video Anomaly DetectiononHR-Avenue
AUC· 2019-12-26
58.1
best: 89.4 (TrajREC)
Graph Embedded Pose Clustering for Anomaly Detection arXiv:1912.11850
Video Anomaly DetectiononHR-UBnormal
AUC· 2019-12-26
55.2
best: 68.4 (MoCoDAD)
Graph Embedded Pose Clustering for Anomaly Detection arXiv:1912.11850
Video UnderstandingonVFP290K
ROC AUC
64.03
best: 96.02 (MPED-RNN (with memory extension))
VideoonVFP290K
ROC AUC
64.03
best: 96.02 (MPED-RNN (with memory extension))

Methodology5 results

Anomaly DetectiononPHEVA
AUC-ROC· 2024-08-26
62.25
best: 76.05 (MPED-RNN)
PHEVA: A Privacy-preserving Human-centric Video Anomaly Detection Dataset arXiv:2408.14329
Anomaly DetectiononHR-ShanghaiTech
AUC· 2019-12-26
74.8
best: 87.23 (PoseWatch-H)
Graph Embedded Pose Clustering for Anomaly Detection arXiv:1912.11850
Anomaly DetectiononHR-Avenue
AUC· 2019-12-26
58.1
best: 89.4 (TrajREC)
Graph Embedded Pose Clustering for Anomaly Detection arXiv:1912.11850
Anomaly DetectiononHR-UBnormal
AUC· 2019-12-26
55.2
best: 68.4 (MoCoDAD)
Graph Embedded Pose Clustering for Anomaly Detection arXiv:1912.11850
Anomaly DetectiononVFP290K
ROC AUC
64.03
best: 96.02 (MPED-RNN (with memory extension))