Visual Prompting Meets Feature Reconstruction-Based Anomaly Detection with Dual-Teacher Supervision 事件

Visual Prompting Meets Feature Reconstruction-Based Anomaly Detection with Dual-Teacher Supervision arXiv:2606.09670v1 Announce Type: new Abstract: Recent Anomaly Detection methods achieve perfect detection and segmentation scores on well-established datasets, such as MVTec. However, many of these methods face challenges when foundational assumptions - such as consistent object scale, viewpoint, background, illumination, and centered placement - are violated. Those variations that occur render