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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.CV2024
AUPIMO: Redefining Visual Anomaly Detection Benchmarks with High Speed and Low Tolerance
Joao P. C. Bertoldo, Dick Ameln, Ashwin Vaidya +1
Recent advances in visual anomaly detection research have seen AUROC and AUPRO scores on public benchmark datasets such as MVTec and VisA converge towards perfect recall, giving th…