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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 TitleRepository
DRA95.9Catching Both Gray and Black Swans: Open-set Supervised Anomaly Detection
CPR99.7Target before Shooting: Accurate Anomaly Detection and Localization under One Millisecond via Cascade Patch Retrieval
BGAD99.3Explicit Boundary Guided Semi-Push-Pull Contrastive Learning for Supervised Anomaly Detection
DevNet94.5Explainable Deep Few-shot Anomaly Detection with Deviation Networks
WeakREST-Block99.8Industrial Anomaly Detection and Localization Using Weakly-Supervised Residual Transformers-
ADClick99.6Towards Efficient Pixel Labeling for Industrial Anomaly Detection and Localization-
PRN99.4Prototypical Residual Networks for Anomaly Detection and Localization-
FLOS93.9Explainable Deep Few-shot Anomaly Detection with Deviation Networks
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