Rethinking Continual Anomaly Detection on the Edge: Benchmarking Under Realistic Industrial Conditions

In three linesNew arXiv paper proposing DINOSaur, a training-free method for continual anomaly detection in industrial settings. Combines frozen DINOv3 backbone, spatially-indexed coreset memory, and neighborhood-restricted anomaly scoring. Achieves zero forgetting, outperforms all baselines across 5 protocols, runs <100ms inference on Jetson Orin Nano with on-device adaptation <30s.

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