3 papers
cs.CV2025
Collaborative Reconstruction and Repair for Multi-class Industrial Anomaly Detection
Qishan Wang, Haofeng Wang, Shuyong Gao +5
Industrial anomaly detection is a challenging open-set task that aims to identify unknown anomalous patterns deviating from normal data distribution. To avoid the significant memor…
cs.CV2025
ADNet: A Large-Scale and Extensible Multi-Domain Benchmark for Anomaly Detection Across 380 Real-World Categories
Hai Ling, Jia Guo, Zhulin Tao +6
Anomaly detection (AD) aims to identify defects using normal-only training data. Existing anomaly detection benchmarks (e.g., MVTec-AD with 15 categories) cover only a narrow range…
cs.CV2025
Search is All You Need for Few-shot Anomaly Detection
Qishan Wang, Jia Guo, Shuyong Gao +5
Few-shot anomaly detection (FSAD) has emerged as a crucial yet challenging task in industrial inspection, where normal distribution modeling must be accomplished with only a few no…