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Models/Learning Causal Temporal Relation and Feature Discrimination for Anomaly Detection

Learning Causal Temporal Relation and Feature Discrimination for Anomaly Detection

Reported on 3 benchmarks across 3 tasks · 1 paper · 3 SOTA

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

Computer Vision4 results

Video UnderstandingonShanghaiTech Weakly Supervised
AUC-ROC· 2021-01-25
97.48
best: 98.14 (PEL)
SOTA
Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning arXiv:2101.10030
VideoonShanghaiTech Weakly Supervised
AUC-ROC· 2021-01-25
97.48
best: 98.14 (PEL)
SOTA
Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning arXiv:2101.10030
Video UnderstandingonShanghaiTech Weakly Supervised
AUC-ROC· 2021-01-25
97.48
best: 98.14 (PEL)
Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning arXiv:2101.10030
VideoonShanghaiTech Weakly Supervised
AUC-ROC· 2021-01-25
97.48
best: 98.14 (PEL)
Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning arXiv:2101.10030

Methodology2 results

Anomaly DetectiononShanghaiTech Weakly Supervised
AUC-ROC· 2021-01-25
97.48
best: 98.14 (PEL)
SOTA
Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning arXiv:2101.10030
Anomaly DetectiononShanghaiTech Weakly Supervised
AUC-ROC· 2021-01-25
97.48
best: 98.14 (PEL)
Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning arXiv:2101.10030