AnomalyGPT

Synthetic anomaly data: Simulates anomalous images and textual descriptions to generate training data, addressing the scarcity of real anomaly examples in industrial settings.

Image decoder + prompt learner: Combines an image decoder with a prompt learner to detect and localize anomalies in product images.

Few-shot ICL: Demonstrates few-shot in-context learning capabilities, adapting to new product types from a handful of examples.

SoTA on industrial benchmarks: Achieves state-of-the-art performance on standard industrial anomaly-detection benchmarks, validating the VLM approach for manufacturing QA.