3D Anomaly Detection

3D Anomaly Detection is a task focused on identifying anomalous objects or regions that deviate from normal patterns within 3D data. This involves analyzing data structures such as 3D point clouds, meshes, or voxels. The task holds significant application value in areas like industrial inspection, autonomous driving, and medical imaging analysis, enhancing detection accuracy and efficiency while reducing false alarm rates. Under the Methodology framework, 3D Anomaly Detection employs advanced algorithms and techniques to achieve efficient processing and precise analysis of complex 3D data.