ADer: A Comprehensive Benchmark for Multi-class Visual Anomaly Detection
ADer: A Comprehensive Benchmark for Multi-class Visual Anomaly Detection
Visual anomaly detection aims to identify anomalous regions in images through unsupervised learning paradigms, with increasing application demand and value in fields such as industrial inspection and medical lesion detection. Despite significant progress in recent years, there is a lack of comprehensive benchmarks to adequately evaluate the performance of various …