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cs.CV2026
Focus and Supplement: Dual-Enhanced Vision Transformer for Multi-Class Anomaly Classification
Xurui Li, Enjie Xu, Chenzhou Li +4
Multi-class anomaly classification in industrial vision remains challenging due to noisy/incomplete anomaly representations and the unknown number of anomaly classes. To overcome t…
cs.CV2025
AnoRefiner: Anomaly-Aware Group-Wise Refinement for Zero-Shot Industrial Anomaly Detection
Dayou Huang, Feng Xue, Xurui Li +1
Zero-shot industrial anomaly detection (ZSAD) methods typically yield coarse anomaly maps as vision transformers (ViTs) extract patch-level features only. To solve this, recent sol…