Results 1 to 10 of about 17,399 (204)

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

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   +2 more sources

Partition-Based Point Cloud Completion Network with Density Refinement [PDF]

Entropy, 2023
In this paper, we propose a novel method for point cloud complementation called PADPNet. Our approach uses a combination of global and local information to infer missing elements in the point cloud.
Jianxin Li, Guannan Si, Xinyu Liang, Zhaoliang An, Pengxin Tian, Fengyu Zhou   +5 more
doaj   +2 more sources

Point Cloud Completion Network Applied to Vehicle Data [PDF]

Sensors, 2022
With the development of autonomous driving, augmented reality, and other fields, it is becoming increasingly important for machines to more accurately and comprehensively perceive their surrounding environment.
Xuehan Ma, Xueyan Li, Junfeng Song
doaj   +2 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   +3 more sources

Structure-Preserving Point Cloud Completion with Symmetry-Guided Progressive Refinement [PDF]

Sensors
Point cloud completion from partial observations remains challenging due to the trade-off between preserving global structural consistency and recovering fine-grained local details, especially under severe incompleteness.
Shuanfeng Zhao, Yixin Niu
doaj   +2 more sources

Semantic Segmentation Method for Sparse Point Clouds Based on Straight Flow Completion and Multi-Feature Fusion [PDF]

Sensors
Point cloud semantic segmentation is a vital task in 3D computer vision. However, the inherent sparsity of point clouds complicates the segmentation process.
Tong Zheng, Zhiyuan Meng, Chongchong Yu, Tao Xie, Yewang Xu   +4 more
doaj   +2 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   +3 more sources

Point Cloud Completion Network Based on Multi-Dimensional Adaptive Feature Fusion and Informative Channel Attention Mechanism [PDF]

Sensors
With the continuous advancement of 3D perception technology, point cloud data has found increasingly widespread application. However, the presence of holes in point cloud data caused by device limitations and environmental interference severely restricts
Di Tian, Jiahang Shi, Jiabo Li, Mingming Gong   +3 more
doaj   +2 more sources