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Found 3 papers, 2 papers with code
Divide and Conquer: High-Resolution Industrial Anomaly Detection via Memory Efficient Tiled Ensemble
To overcome this challenge, we present the tiled ensemble approach, which reduces memory consumption by dividing the input images into a grid of tiles and training a dedicated model for each tile location.
AUPIMO: Redefining Visual Anomaly Detection Benchmarks with High Speed and Low Tolerance
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.
Anomalib: A Deep Learning Library for Anomaly Detection
This paper introduces anomalib, a novel library for unsupervised anomaly detection and localization.
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