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cs.CV2025
Multi-class Image Anomaly Detection for Practical Applications: Requirements and Robust Solutions
Jaehyuk Heo, Pilsung Kang
Recent advances in image anomaly detection have extended unsupervised learning-based models from single-class settings to multi-class frameworks, aiming to improve efficiency in tr…
cs.CV2025
Domain Adaptation of Attention Heads for Zero-shot Anomaly Detection
Kiyoon Jeong, Jaehyuk Heo, Junyeong Son +1
Zero-shot anomaly detection (ZSAD) enables anomaly detection without normal samples from target categories, addressing scenarios where task-specific training data is unavailable. H…