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cs.CV2025
From Benchmarks to Reality: Advancing Visual Anomaly Detection by the VAND 3.0 Challenge
Lars Heckler-Kram, Ashwin Vaidya, Jan-Hendrik Neudeck +4
Visual anomaly detection is a strongly application-driven field of research. Consequently, the connection between academia and industry is of paramount importance. In this regard,…
cs.CV2025
Beyond Academic Benchmarks: Critical Analysis and Best Practices for Visual Industrial Anomaly Detection
Aimira Baitieva, Yacine Bouaouni, Alexandre Briot +3
Anomaly detection (AD) is essential for automating visual inspection in manufacturing. This field of computer vision is rapidly evolving, with increasing attention towards real-wor…