Current 3D anomaly detection techniques often prove insufficient for noisy industrial scans. In a new study, researchers from Shibaura Institute of Technology, Japan, and FPT University, Vietnam, have developed Vote3D-AD as an innovative solution. The single-pass framework trains exclusively on defect-free data and utilizes the Varied Defect Synthesis pseudo-anomaly generator and a vote-and-cluster architecture to outperform state-of-the-art alternatives on various benchmarks. It is expected to further streamline inspection pipelines.