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SotA/Methodology/Anomaly Detection/BTAD

Anomaly Detection on BTAD

Metric: Segmentation AUROC (higher is better)

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#Model↕Segmentation AUROC▼AugmentationsPaperDate↕Code
1WeakREST-Block99.3YesIndustrial Anomaly Detection and Localization Us...2023-06-06-
2CPR99.1NoTarget before Shooting: Accurate Anomaly Detecti...2023-08-13Code
3WeakREST-Un98.7YesIndustrial Anomaly Detection and Localization Us...2023-06-06-
4CPR98.4NoTarget before Shooting: Accurate Anomaly Detecti...2023-08-13Code
5FastFlow+AltUB98.2YesAltUB: Alternating Training Method to Update Bas...2022-10-26-
6URD98.1YesUnlocking the Potential of Reverse Distillation ...2024-12-10Code
7RealNet97.9YesRealNet: A Feature Selection Network with Realis...2024-03-09Code
8PNI97.8YesPNI : Industrial Anomaly Detection using Positio...2022-11-22Code
9UniNet97.7No--Code
10PyramidFlow (Res18)97.7YesPyramidFlow: High-Resolution Defect Contrastive ...2023-03-05-
11Reverse Distillation ++97.43No--Code
12MuSc (zero-shot)97.35NoMuSc: Zero-Shot Industrial Anomaly Classificatio...2024-01-30Code
13AD-CLSCNFs97.13No--Code
14PatchSVDD93.1YesPatch SVDD: Patch-level SVDD for Anomaly Detecti...2020-06-29Code
15VT-ADL81.8YesVT-ADL: A Vision Transformer Network for Image A...2021-04-20Code