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Supervised Anomaly Detection On Mvtec Ad

评估指标

Detection AUROC

评测结果

各个模型在此基准测试上的表现结果

模型名称	Detection AUROC	Paper Title	Repository
DRA	95.9	Catching Both Gray and Black Swans: Open-set Supervised Anomaly Detection	-
CPR	99.7	Target before Shooting: Accurate Anomaly Detection and Localization under One Millisecond via Cascade Patch Retrieval	-
BGAD	99.3	Explicit Boundary Guided Semi-Push-Pull Contrastive Learning for Supervised Anomaly Detection	-
DevNet	94.5	Explainable Deep Few-shot Anomaly Detection with Deviation Networks	-
WeakREST-Block	99.8	Industrial Anomaly Detection and Localization Using Weakly-Supervised Residual Transformers	-
ADClick	99.6	Towards Efficient Pixel Labeling for Industrial Anomaly Detection and Localization	-
PRN	99.4	Prototypical Residual Networks for Anomaly Detection and Localization	-
FLOS	93.9	Explainable Deep Few-shot Anomaly Detection with Deviation Networks	-

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Supervised Anomaly Detection On Mvtec Ad | SOTA | HyperAI超神经