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SotA/Methodology/Anomaly Detection/MPDD

Anomaly Detection on MPDD

Metric: Segmentation AUROC (higher is better)

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#Model↕Segmentation AUROC▼AugmentationsPaperDate↕Code
1GLASS99.4NoA Unified Anomaly Synthesis Strategy with Gradie...2024-07-12Code
2Dinomaly99.1NoDinomaly: The Less Is More Philosophy in Multi-C...2024-05-23Code
3DMDD98.96NoDual-Modeling Decouple Distillation for Unsuperv...2024-08-07-
4PBAS98.8NoProgressive Boundary Guided Anomaly Synthesis fo...2024-12-23Code
5CRAS98.7NoCenter-aware Residual Anomaly Synthesis for Mult...2025-05-23Code
6GLAD98.7NoGLAD: Towards Better Reconstruction with Global ...2024-06-11Code
7DiffusionAD98.5NoDiffusionAD: Norm-guided One-step Denoising Diff...2023-03-15Code
8KAnoCLIP98.3NoKAnoCLIP: Zero-Shot Anomaly Detection through Kn...2025-01-07-
9RealNet98.2YesRealNet: A Feature Selection Network with Realis...2024-03-09Code
10FastRecon97.9No---
11LeMO97.8NoTowards Total Online Unsupervised Anomaly Detect...2023-05-25-
12ULSAD97.45NoRevisiting Deep Feature Reconstruction for Logic...2024-10-21Code
13ADSPR96.8No--Code
14AdaCLIP96.1NoAdaCLIP: Adapting CLIP with Hybrid Learnable Pro...2024-07-22Code
15PatchCore95.66NoTowards Total Recall in Industrial Anomaly Detec...2021-06-15Code