Changchun Institute of Optics,Fine Mechanics and Physics,CAS
Multistage Adaptive Point-Growth Network for Dense Point Cloud Completion | |
R. D. Hao; Z. H. Wei; X. He; K. F. Zhu; J. Wang; J. W. He and L. Zhang | |
2022 | |
发表期刊 | Remote Sensing |
卷号 | 14期号:20页码:19 |
摘要 | The point cloud data from actual measurements are often sparse and incomplete, making it difficult to apply them directly to visual processing and 3D reconstruction. The point cloud completion task can predict missing parts based on a sparse and incomplete point cloud model. However, the disordered and unstructured characteristics of point clouds make it difficult for neural networks to obtain detailed spatial structures and topological relationships, resulting in a challenging point cloud completion task. Existing point cloud completion methods can only predict the rough geometry of the point cloud, but cannot accurately predict the local details. To address the shortcomings of existing point cloud complementation methods, this paper describes a novel network for adaptive point cloud growth, MAPGNet, which generates a sparse skeletal point cloud using the skeletal features in the composite encoder, and then adaptively grows the local point cloud in the spherical neighborhood of each point using the growth features to complement the details of the point cloud in two steps. In this paper, the Offset Transformer module is added in the process of complementation to enhance the contextual connection between point clouds. As a result, MAPGNet improves the quality of the generated point clouds and recovers more local detail information. Comparing our algorithm with other state-of-the-art algorithms in different datasets, experimental results show that our algorithm has advantages in dense point cloud completion. |
DOI | 10.3390/rs14205214 |
URL | 查看原文 |
收录类别 | sci ; ei |
语种 | 英语 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ciomp.ac.cn/handle/181722/66886 |
专题 | 中国科学院长春光学精密机械与物理研究所 |
推荐引用方式 GB/T 7714 | R. D. Hao,Z. H. Wei,X. He,et al. Multistage Adaptive Point-Growth Network for Dense Point Cloud Completion[J]. Remote Sensing,2022,14(20):19. |
APA | R. D. Hao,Z. H. Wei,X. He,K. F. Zhu,J. Wang,&J. W. He and L. Zhang.(2022).Multistage Adaptive Point-Growth Network for Dense Point Cloud Completion.Remote Sensing,14(20),19. |
MLA | R. D. Hao,et al."Multistage Adaptive Point-Growth Network for Dense Point Cloud Completion".Remote Sensing 14.20(2022):19. |
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