3 papers
cs.CV2026
OSAGEN: Object-Aware Mask Priors and Multistage Decoupled Diffusion for Industrial Anomaly Generation
Jinyi Xu, Peng Chen, Yunkang Cao +3
Industrial anomaly detection and localization are limited by scarce real anomalies and pixel-level annotations, a bottleneck that synthetic image-mask pairs can alleviate. However,…
cs.CV2026
Towards Explainable Industrial Anomaly Detection via Knowledge-Guided Latent Reasoning
Peng Chen, Chao Huang, Yunkang Cao +7
Industrial anomaly detection demands precise reasoning over fine-grained defect patterns. However, existing multimodal large language models (MLLMs), pretrained on general-domain d…
cs.CV2025
IAD-R1: Reinforcing Consistent Reasoning in Industrial Anomaly Detection
Yanhui Li, Yunkang Cao, Chengliang Liu +3
Industrial anomaly detection is a critical component of modern manufacturing, yet the scarcity of defective samples restricts traditional detection methods to scenario-specific app…