Industrial Anomaly Detection

Industrial anomaly detection focuses on automatically identifying defects in manufacturing processes using computer vision, aiming for high accuracy and efficiency. Current research emphasizes robust methods that handle noisy real-world data, leveraging multimodal data (RGB images, 3D point clouds), and exploring novel architectures like large language models and diffusion models for improved anomaly detection and localization. These advancements are crucial for improving quality control, reducing production costs, and enhancing the safety and reliability of industrial systems.