FiSeCLIP achieves state-of-the-art zero-shot anomaly detection by using a batch of test images as mutual references and filtering noisy features with text-guided masks, without any training.
The mvtec anomaly detection dataset: a comprehensive real-world dataset for unsupervised anomaly detection
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Bridge Feature Matching and Cross-Modal Alignment with Mutual-filtering for Zero-shot Anomaly Detection
FiSeCLIP achieves state-of-the-art zero-shot anomaly detection by using a batch of test images as mutual references and filtering noisy features with text-guided masks, without any training.