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cs.CV2026
Dual Prototype-Conditioned Diffusion Model for Scalable Multi-Class Unsupervised Anomaly Detection in Large Category Spaces
Yaoxuan Feng, Yuxin Li, Weijiang Lv +5
Multi-class anomaly detection aims to build unified models across diverse product categories. However, as the number of categories grows, its performance often degrades due to incr…
cs.CV2025
FastRef:Fast Prototype Refinement for Few-Shot Industrial Anomaly Detection
Long Tian, Yufei Li, Yuyang Dai +3
Few-shot industrial anomaly detection (FS-IAD) presents a critical challenge for practical automated inspection systems operating in data-scarce environments. While existing approa…