HyperAI

Anomaly Detection In Surveillance Videos On

المقاييس

Decidability
EER
ROC AUC

النتائج

نتائج أداء النماذج المختلفة على هذا المعيار القياسي

جدول المقارنة
اسم النموذجDecidabilityEERROC AUC
weakly-and-partially-supervised-learning0.8850.30275.90
contrastive-regularized-u-net-for-video--85.24
stead-spatio-temporal-efficient-anomaly-1--88.87
mulde-multiscale-log-density-estimation-via--78.5%
stead-spatio-temporal-efficient-anomaly-1--91.34
a-multi-stream-deep-neural-network-with-late--84.48
mgfn-magnitude-contrastive-glance-and-focus--86.98
mist-multiple-instance-self-training--82.30
real-world-anomaly-detection-in-surveillance0.6130.35375.41
3d-resnet-with-ranking-loss-function-for--76.67
learning-prompt-enhanced-context-features-for--86.76
weakly-supervised-video-anomaly-detection--84.03
self-supervised-sparse-representation-for--85.99
multiple-instance-based-video-anomaly--80.10
batchnorm-based-weakly-supervised-video--87.24
anomalous-event-recognition-in-videos-based--81.91
localizing-anomalies-from-weakly-labeled--85.38