SoftPatch: A Memory-Based Unsupervised Anomaly Detection AD Method that Efficiently Denoises the Data at the Patch Level

SoftPatch is a novel algorithm for unsupervised anomaly detection that efficiently denoises data at the patch level. It outperforms state-of-the-art methods on benchmark datasets and highlights the importance of investigating noisy data in anomaly detection.