The present application relates to the technical field of artificial intelligence. Disclosed are a three-dimensional point cloud semantic segmentation method and apparatus, and a device and a medium. The method comprises: performing, by using a pre-set spatial cell, point cloud division and quantitative discrimination on three-dimensional point cloud data to be subjected to prediction, so as to obtain target point cloud data; inputting the target point cloud data into a point cloud semantic category prediction model for semantic category probability prediction, so as to obtain a point cloud semantic category probability prediction value of the target point cloud data, wherein the point cloud semantic category prediction model is a model obtained by means of training on the basis of a PointSIFT neural network module and a PointNet++ neural network; and determining a target semantic category of each point in the target point cloud data according to the point cloud semantic category probability prediction value. Fast and accurate logical division for point clouds of a complex large-scale target object is realized, thereby improving the recognition precision of point cloud segmentation; and fine features of the complex target object can be better processed, thereby improving the accuracy of semantic category prediction.
THREE-DIMENSIONAL POINT CLOUD SEMANTIC SEGMENTATION METHOD AND APPARATUS, AND DEVICE AND MEDIUM