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SOTA
Anomaly Classification
Anomaly Classification On Goodsad
Anomaly Classification On Goodsad
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AUPR
AUROC
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Columns
Modellname
AUPR
AUROC
Paper Title
Repository
PatchCore-100%
86.1
85.5
Towards Total Recall in Industrial Anomaly Detection
PatchCore-1%
83.3
81.4
Towards Total Recall in Industrial Anomaly Detection
SimpleNet
78.7
75.3
SimpleNet: A Simple Network for Image Anomaly Detection and Localization
RD4AD
68.2
66.5
Anomaly Detection via Reverse Distillation from One-Class Embedding
DRAEM
71
65.9
DRAEM -- A discriminatively trained reconstruction embedding for surface anomaly detection
SPADE
68.7
64.1
Sub-Image Anomaly Detection with Deep Pyramid Correspondences
NSA
71.8
67.3
Natural Synthetic Anomalies for Self-Supervised Anomaly Detection and Localization
CFLOW-AD
75.3
71.2
CFLOW-AD: Real-Time Unsupervised Anomaly Detection with Localization via Conditional Normalizing Flows
MiniMaxAD-fr
-
86.1
MiniMaxAD: A Lightweight Autoencoder for Feature-Rich Anomaly Detection
-
CutPaste
62.8
60.2
CutPaste: Self-Supervised Learning for Anomaly Detection and Localization
f-AnoGAN
66.6
62.8
f-AnoGAN: Fast Unsupervised Anomaly Detection with Generative Adversarial Networks
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