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A Survey of Point Cloud Completion

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Point cloud completion is able to estimate the complete point cloud starting from the missing point cloud, which obtains higher quality point cloud data for widely used in remote sensing 3-D modeling, medical imaging, robot vision, etc.
Zhiyun Zhuang, Zhiyang Zhi, Ting Han, Yiping Chen, Jun Chen, Cheng Wang, Ming Cheng, Xinchang Zhang, Nannan Qin, Lingfei Ma   +9 more
doaj   +6 more sources

Data-Driven Point Cloud Objects Completion [PDF]

Sensors, 2019
With the development of the laser scanning technique, it is easier to obtain 3D large-scale scene rapidly. However, many scanned objects may suffer serious incompletion caused by the scanning angles or occlusion, which has severely impacted their future ...
Yang Zhang, Zhen Liu, Xiang Li, Yu Zang
doaj   +6 more sources

Learning Contours for Point Cloud Completion

Remote Sensing, 2023
The integrity of a point cloud frequently suffers from discontinuous material surfaces or coarse sensor resolutions. Existing methods focus on reconstructing the overall structure, but salient points or small irregular surfaces are difficult to be ...
Jiabo Xu, Zeyun Wan, Jingbo Wei
doaj   +5 more sources

End-to-End Point Cloud Completion Network with Attention Mechanism [PDF]

Sensors, 2022
We propose a conceptually simple, general framework and end-to-end approach to point cloud completion, entitled PCA-Net. This approach differs from the existing methods in that it does not require a “simple” network, such as multilayer perceptrons (MLPs),
Yaqin Li, Binbin Han, Shan Zeng, Shengyong Xu, Cao Yuan   +4 more
doaj   +3 more sources

Deep-learning-based point cloud completion methods: A review

Graphical Models
Point cloud completion aims to utilize algorithms to repair missing parts in 3D data for high-quality point clouds. This technology is crucial for applications such as autonomous driving and urban planning.
Kun Zhang, Ao Zhang, Xiaohong Wang, Weisong Li   +3 more
doaj   +4 more sources

A Partial Point Cloud Completion Network Focusing on Detail Reconstruction

Remote Sensing, 2023
The point cloud is disordered and unstructured, and it is difficult to extract detailed features. The detailed part of the target shape is difficult to complete in the point cloud completion task.
Ming Wei, Jiaqi Sun, Yaoyuan Zhang, Ming Zhu, Haitao Nie, Huiying Liu, Jiarong Wang   +6 more
doaj   +4 more sources

Multistage Adaptive Point-Growth Network for Dense Point Cloud Completion

Remote Sensing, 2022
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.
Ruidong Hao, Zhonghui Wei, Xu He, Kaifeng Zhu, Jun Wang, Jiawei He, Lei Zhang   +6 more
doaj   +2 more sources

Part-Aware Point Cloud Completion through Multi-Modal Part Segmentation [PDF]

Entropy, 2023
Point cloud completion aims to generate high-resolution point clouds using incomplete point clouds as input and is the foundational task for many 3D visual applications.
Fuyang Yu, Runze Tian, Xuanjun Wang, Xiaohui Liang   +3 more
doaj   +2 more sources

Colored Point Cloud Completion for a Head Using Adversarial Rendered Image Loss [PDF]

Journal of Imaging, 2022
Recent advances in depth measurement and its utilization have made point cloud processing more critical. Additionally, the human head is essential for communication, and its three-dimensional data are expected to be utilized in this regard.
Yuki Ishida, Yoshitsugu Manabe, Noriko Yata   +2 more
doaj   +2 more sources

Cyclic Global Guiding Network for Point Cloud Completion

Remote Sensing, 2022
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
Ming Wei, Ming Zhu, Yaoyuan Zhang, Jiaqi Sun, Jiarong Wang   +4 more
doaj   +3 more sources