PASTA uses ViT feature distribution analysis and SAM to achieve up to 88.3% target and 63.5% anomaly IoU with 75.8% reduced training time under weak image-level supervision on custom datasets.
Aa-clip: Enhancing zero-shot anomaly detection via anomaly-aware clip,
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PASTA: Vision Transformer Patch Aggregation for Weakly Supervised Target and Anomaly Segmentation
PASTA uses ViT feature distribution analysis and SAM to achieve up to 88.3% target and 63.5% anomaly IoU with 75.8% reduced training time under weak image-level supervision on custom datasets.