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Models/Video Level features kNN

Video Level features kNN

Reported on 6 benchmarks across 3 tasks · 1 paper

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

Computer Vision4 results

Abnormal Event Detection In VideoonPHANTOM
Avg. ROC-AUC· uses extra data· 2021-12-14
0.76
best: 0.78 (Pooled Image Level kNN)
Approaches Toward Physical and General Video Anomaly Detection arXiv:2112.07661
Abnormal Event Detection In VideoonSomething-Something V2
Avg. ROC-AUC· uses extra data· 2021-12-14
0.52
best: 0.58 (Pooled Image Level kNN)
Approaches Toward Physical and General Video Anomaly Detection arXiv:2112.07661
Semi-supervised Anomaly DetectiononPHANTOM
Avg. ROC-AUC· uses extra data· 2021-12-14
0.76
best: 0.78 (Pooled Image Level kNN)
Approaches Toward Physical and General Video Anomaly Detection arXiv:2112.07661
Semi-supervised Anomaly DetectiononSomething-Something V2
Avg. ROC-AUC· uses extra data· 2021-12-14
0.52
best: 0.58 (Pooled Image Level kNN)
Approaches Toward Physical and General Video Anomaly Detection arXiv:2112.07661

Methodology2 results

Anomaly DetectiononPHANTOM
Avg. ROC-AUC· uses extra data· 2021-12-14
0.76
best: 0.78 (Pooled Image Level kNN)
Approaches Toward Physical and General Video Anomaly Detection arXiv:2112.07661
Anomaly DetectiononSomething-Something V2
Avg. ROC-AUC· uses extra data· 2021-12-14
0.52
best: 0.58 (Pooled Image Level kNN)
Approaches Toward Physical and General Video Anomaly Detection arXiv:2112.07661