1 code implementation • 3 Jan 2024 • Joao P. C. Bertoldo, Dick Ameln, Ashwin Vaidya, Samet Akçay
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 the impression that these benchmarks are near-solved.
no code implementations • 23 Jan 2023 • Joao P. C. Bertoldo, Santiago Velasco-Forero, Jesus Angulo, Etienne Decencière
We propose an incremental improvement to Fully Convolutional Data Description (FCDD), an adaptation of the one-class classification approach from anomaly detection to image anomaly segmentation (a. k. a.
no code implementations • 6 Jun 2022 • Joao P. C. Bertoldo, Etienne Decencière
Fully Convolutional Data Description (FCDD), an explainable version of the Hypersphere Classifier (HSC), directly addresses image anomaly detection (AD) and pixel-wise AD without any post-hoc explainer methods.