Existing algorithms for 3D point cloud MAE suffer from issues such as position information leakage and lack of diversity in modes.To address these problems,this paper proposes a PIP-MAE algorithm for point cloud-image-point cloud MAE.The algorithm guides the 3D point cloud pre-training model by enriching 2D image knowledge,randomly masks the input 3D point cloud and its projected 2D image,and then reconstructs the masked information for both modes.The experiments on downstream tasks validate the effectiveness of the PIP-MAE algorithm,and it improves accuracy of these downstream tasks,which can be widely used in various types of downstream tasks.
Deep Learningpoint cloud reconstructionpoint cloud classificationpoint cloud segmentation
国家科技期刊平台
NSTL
万方数据
维普
