ULSAD

Reported on 3 benchmarks across 1 task · 1 paper

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Methodology3 results

Anomaly DetectiononMPDD
Detection AUROC· 2024-10-21
95.73
best: 99.6 (GLASS)
Revisiting Deep Feature Reconstruction for Logical and Structural Industrial Anomaly Detection arXiv:2410.16255
Anomaly DetectiononMPDD
Segmentation AUPRO· 2024-10-21
92.02
best: 98.2 (GLASS)
Revisiting Deep Feature Reconstruction for Logical and Structural Industrial Anomaly Detection arXiv:2410.16255
Anomaly DetectiononMPDD
Segmentation AUROC· 2024-10-21
97.45
best: 99.4 (GLASS)
Revisiting Deep Feature Reconstruction for Logical and Structural Industrial Anomaly Detection arXiv:2410.16255