Shi-Lei Zeng

Focus and Supplement: Dual-Enhanced Vision Transformer for Multi-Class Anomaly Classification

Multi-class anomaly classification in industrial vision remains challenging due to noisy/incomplete anomaly representations and the unknown number of anomaly classes. To overcome this, we propose MACO, a novel multi-class anomaly classification framework that learns comprehensive representations and dynamically estimat...