FEW-SHOT POINT CLOUD SEMANTIC SEGMENTATION METHOD, AND NETWORK, STORAGE MEDIUM AND PROCESSOR

The present application is applicable to the technical field of point cloud semantic segmentation. Provided are a few-shot point cloud semantic segmentation method, and a network, a storage medium and a processor. In the few-shot point cloud semantic segmentation method, extracted pseudo prototype features adapted to query set data are propagated by using labels, such that prototype features adapted to the query set data are acquired, and feature calibration is performed by means of extracting the relationship between prototypes and the query set data. During prototype augmentation, distribution information of the query set data and prototype information of a support set are effectively used. The adaptability of the prototypes to the query set data is further improved. Therefore, the present invention can obtain prototype features adapted to a query set, thereby implementing effective segmentation of a point cloud scene, and reducing the impact of an erroneous judgment result on augmented prototypes. La prése