Point cloud up-sampling method based on GAN network

The invention discloses a point cloud up-sampling method based on a GAN network. A GAN network composed of a Generator and a Display discriminator is mainly used for carrying out the point cloud up-sampling. The Generator is composed of an annular arrangement module, a multi-frequency pooling module and a GRU network module, and can effectively learn the geometrical characteristics and global characteristics of each point in the point cloud, thereby better mastering the geometrical information of the input point cloud. The discriminator Discriminator is composed of two layers of feature extractors and a deconvolution network module, can discriminate whether the input point cloud is true or false, and helps to better optimize the GAN network. Through annular arrangement, disordered point neighborhoods can be arranged into an ordered annular structure through orthogonal projection and counterclockwise arrangement, and geometrical characteristics of different groups of neighborhoods of each point can be accurate