22 citations · 22 across the 8 of their papers we have counts for
Showing 2026Show all
3 papers · 1 filter
cs.CV2026
ConceptADapt: Concept-guided Adaptive Feature Reconstruction with Dynamic Attention for Few-Shot Industrial Anomaly Detection
Yufei Li, Yicheng Ruan, Long Tian +2
Few-shot industrial anomaly detection (FS-IAD) focuses on detecting and localizing visual defects in industrial inspection during the cold-start phase, where only a limited number…
cs.CV2026
One-Step Diffusion with Inverse Residual Fields for Unsupervised Industrial Anomaly Detection
Boan Zhang, Wen Li, Guanhua Yu +3
Diffusion models have achieved outstanding performance in unsupervised industrial anomaly detection (uIAD) by learning a manifold of normal data under the common assumption that of…
cs.LG2026
Enhancing few-shot time series forecasting with LLM-guided diffusion
Haonan Shi, Dehua Shuai, Liming Wang +2
Time series forecasting in specialized domains is often constrained by limited data availability, where conventional models typically require large-scale datasets to effectively ca…