Cyclic Global Guiding Network for Point Cloud Completion

doi:10.3390/rs14143316

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	Cyclic Global Guiding Network for Point Cloud Completion
	M. Wei; M. Zhu; Y. Y. Zhang; J. Q. Sun and J. R. Wang
刊名	Remote Sensing
	2022
卷号	14 期号:14 页码:19
DOI	10.3390/rs14143316
英文摘要	The application of 3D scenes has gradually expanded in recent years. A 3D point cloud is unreliable when it is acquired because of the performance of the sensor. Therefore, it causes difficulties in utilization. Point cloud completion can reconstruct and restore sparse and incomplete point clouds to a more realistic shape. We propose a cyclic global guiding network structure and apply it to point cloud completion tasks. While learning the local details of the whole cloud, our network structure can play a guiding role and will not ignore the overall characteristics of the whole cloud. Based on global guidance, we propose a variety of fitting planes and layered folding attention modules to strengthen the local effect. We use the relationship between the point and the plane to increase the compatibility between the network learning and the original sparse point cloud. We use the attention mechanism of the layer overlay to strengthen the local effect between the encode and decode. Therefore, point clouds are more accurate. Our experiments indicate the effectiveness of our method on the ShapeNet, KITTI, and MVP datasets and are superior to other networks.
URL标识	查看原文
语种	英语
内容类型	期刊论文
源URL	[http://ir.ciomp.ac.cn/handle/181722/66501]
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	M. Wei,M. Zhu,Y. Y. Zhang,et al. Cyclic Global Guiding Network for Point Cloud Completion[J]. Remote Sensing,2022,14(14):19.
APA	M. Wei,M. Zhu,Y. Y. Zhang,&J. Q. Sun and J. R. Wang.(2022).Cyclic Global Guiding Network for Point Cloud Completion.Remote Sensing,14(14),19.
MLA	M. Wei,et al."Cyclic Global Guiding Network for Point Cloud Completion".Remote Sensing 14.14(2022):19.