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Found 2 papers, 0 papers with code
Towards Efficient Pixel Labeling for Industrial Anomaly Detection and Localization
By fine-tuning the ADClick-Seg model using the weak labels inferred by ADClick, we establish the state-of-the-art performances in supervised AD tasks (AP $= 86. 4\%$ on MVTec AD and AP $= 78. 4\%$, PRO $= 98. 6\%$ on KSDD2).
Ranked #3 on
Supervised Anomaly Detection
on MVTec AD
(using extra training data)
Industrial Anomaly Detection and Localization Using Weakly-Supervised Residual Transformers
To leverage this feature, we adapt the Swin Transformer for enhanced anomaly detection and localization.
Ranked #1 on
Unsupervised Anomaly Detection
on KolektorSDD2
(using extra training data)
