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ResearchFormerly WizWand

Anomaly Detection on Eyecandies (AUCP/MF1P)

96.913AUCPUniMMAD
46.1859659.3554872.52585.69452Sep 30, 2025
Updated 8mo ago

Evaluation results

MethodLinks
UniMMADEvaluation Protocol=Unified Multi-modal and Multi-class Model2025.0996.91339.436
CFMEvaluation Protocol=Specialized Models (One model for one dataset), Publications=CVPR20242025.0995.83831.916
AdaCLIPEvaluation Protocol=Generalist Models (One model performs all AD tasks without fine-tuning), Publications=ECCV20242025.0995.17332.047
AA-CLIPEvaluation Protocol=Generalist Models (One model performs all AD tasks without fine-tuning), Publications=CVPR20252025.0994.74427.205
M3DMEvaluation Protocol=Specialized Models (One model for one dataset), Publications=CVPR20232025.0993.75836.527
UniMMADPublications=-, Model Category=Unified Multi-modal and Multi-class Model2025.0985.56684.103
MVFAEvaluation Protocol=Generalist Models (One model performs all AD tasks without fine-tuning), Publications=CVPR20242025.0982.6511.105
CFMPublications=CVPR2024, Model Category=Specialized Models (One model for one dataset)2025.0981.84779.668
M3DMPublications=CVPR2023, Model Category=Specialized Models (One model for one dataset)2025.0977.38776.039
AdaCLIPPublications=ECCV2024, Model Category=Generalist Models (One model performs all AD tasks without fine-tuning)2025.0973.13474.809
MVFAPublications=CVPR2024, Model Category=Generalist Models (One model performs all AD tasks without fine-tuning)2025.0964.81770.268
AA-CLIPPublications=CVPR2025, Model Category=Generalist Models (One model performs all AD tasks without fine-tuning)2025.0948.13765.642