AnomalyDINO-S (full-shot)
Reported on 6 benchmarks across 1 task · 1 paper · 1 SOTA
Note: results are matched by exact model name. Different papers may use the same name for different model variants.
Methodology6 results
- Segmentation AUPRO (until 30% FPR)· 2024-05-23SOTA96.1
- Detection AUROC· 2024-05-2399.5best: 99.9 (GLASS)
- Segmentation AUPRO· 2024-05-2395best: 98.4 (WeakREST-Block)
- Segmentation AUROC· 2024-05-2398.2best: 99.7 (WeakREST-Block)
- Detection AUROC· 2024-05-2397.6best: 99.8 (UniNet)
- Segmentation AUROC· 2024-05-2398.8best: 99.1 (Dinomaly ViT-L (model-unified multi-class))