Cai-Chen Gao

GBA-AD: geometry- and boundary-aware unsupervised anomaly detection for high-resolution 3D point clouds

Unsupervised 3D point-cloud anomaly detection trains exclusively on normal samples and must identify anomalous objects and localize anomalous regions at test time. Although high-resolution, complete point clouds encode fine-grained geometric detail, defects typically affect only a small fraction of the object surface;...