3 accepted papers
Vision-Language Models (VLMs) demonstrate strong general-purpose reasoning but remain limited in physics-grounded anomaly detection, where causal understanding of dynamics is essential. Existing VLMs, trained predominantly on appearance-centric correlations, fail to capture kinematic constraints, le…
Humans detect real-world object anomalies by perceiving, interacting, and reasoning based on object-conditioned physical knowledge. The long-term goal of Industrial Anomaly Detection (IAD) is to enable machines to autonomously replicate this skill. However, current IAD algorithms are largely develop…
Recently 3D anomaly detection a crucial problem involving fine-grained geometry discrimination is getting more attention. However the lack of abundant real 3D anomaly data limits the scalability of current models. To enable scalable anomaly data collection we propose a 3D anomaly synthesis pipeline…