Depth Anomaly Segmentation

Depth Anomaly Segmentation is an anomaly detection technique based on depth information, aiming to identify and segment regions that do not conform to the normal scene by analyzing depth data in three-dimensional space. This task utilizes data obtained from depth sensors, combined with advanced image processing and machine learning algorithms, to achieve precise environmental perception and anomaly monitoring. It is widely applied in industrial inspection, autonomous driving, security surveillance, and other fields, possessing significant practical value.