M-3LAB/awesome-3d-anomaly-detection

This resource collects and categorizes methods for identifying unusual or faulty objects in 3D data, such as point clouds from lidar sensors or depth cameras. It helps researchers and engineers working with 3D scanning systems to quickly find and understand different techniques for detecting anomalies in industrial inspection, quality control, or surveillance. It takes research papers and public datasets as input and provides an organized overview of existing approaches, their strengths, and relevant datasets.