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cs.CV2026
A Feature Shuffling and Restoration Strategy for Universal Unsupervised Anomaly Detection
Wei Luo, Haiming Yao, Zhenfeng Qiang +2
Unsupervised anomaly detection is vital in industrial fields, with reconstruction-based methods favored for their simplicity and effectiveness. However, reconstruction methods ofte…
cs.CV2025
Exploring Intrinsic Normal Prototypes within a Single Image for Universal Anomaly Detection
Wei Luo, Yunkang Cao, Haiming Yao +5
Anomaly detection (AD) is essential for industrial inspection, yet existing methods typically rely on ``comparing'' test images to normal references from a training set. However, v…
cs.CV2023★ 1 cited
Learning Global-Local Correspondence with Semantic Bottleneck for Logical Anomaly Detection
Haiming Yao, Wenyong Yu, Wei Luo +3
This paper presents a novel framework, named Global-Local Correspondence Framework (GLCF), for visual anomaly detection with logical constraints. Visual anomaly detection has becom…