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Point Cloud Completion: A Survey
IEEE Transactions on Visualization and Computer Graphics, Volume: 30, Issue: 10, Pages: 6880 - 6899
Swansea University Authors: Keneni Tesema , Mark Jones , Muneeb Ahmad , Gary Tam
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DOI (Published version): 10.1109/tvcg.2023.3344935
Abstract
Point cloud completion is the task of producing a complete 3D shape given an input of a partial point cloud. It has become a vital process in 3D computer graphics, vision and applications such as autonomous driving, robotics, and augmented reality. These applications often rely on the presence of a...
Published in: | IEEE Transactions on Visualization and Computer Graphics |
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ISSN: | 1077-2626 1941-0506 |
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Institute of Electrical and Electronics Engineers (IEEE)
2024
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It has become a vital process in 3D computer graphics, vision and applications such as autonomous driving, robotics, and augmented reality. These applications often rely on the presence of a complete 3D representation of the environment. Over the past few years, many completion algorithms have been proposed and a substantial amount of research has been carried out. However, there are not many in-depth surveys that summarise the research progress in such a way that allows users to make an informed choice of what algorithms to employ given the type of data they have, the end result they want, the challenges they may face and the possible strategies they could use. In this study, we present a comprehensive survey and classification of papers on point cloud completion until August 2023 based on the strategies, techniques, inputs, outputs, and network architectures. We will also cover datasets, evaluation methods, and application areas in point cloud completion. 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v2 65337 2023-12-18 Point Cloud Completion: A Survey 565d5e98f266077e36258ac9c10b2a80 0009-0003-1247-2435 Keneni Tesema Keneni Tesema true false 2e1030b6e14fc9debd5d5ae7cc335562 0000-0001-8991-1190 Mark Jones Mark Jones true false 9c42fd947397b1ad2bfa9107457974d5 0000-0001-8111-9967 Muneeb Ahmad Muneeb Ahmad true false e75a68e11a20e5f1da94ee6e28ff5e76 0000-0001-7387-5180 Gary Tam Gary Tam true false 2023-12-18 Point cloud completion is the task of producing a complete 3D shape given an input of a partial point cloud. It has become a vital process in 3D computer graphics, vision and applications such as autonomous driving, robotics, and augmented reality. These applications often rely on the presence of a complete 3D representation of the environment. Over the past few years, many completion algorithms have been proposed and a substantial amount of research has been carried out. However, there are not many in-depth surveys that summarise the research progress in such a way that allows users to make an informed choice of what algorithms to employ given the type of data they have, the end result they want, the challenges they may face and the possible strategies they could use. In this study, we present a comprehensive survey and classification of papers on point cloud completion until August 2023 based on the strategies, techniques, inputs, outputs, and network architectures. We will also cover datasets, evaluation methods, and application areas in point cloud completion. Finally, we discuss challenges faced by the research community and future research directions. Journal Article IEEE Transactions on Visualization and Computer Graphics 30 10 6880 6899 Institute of Electrical and Electronics Engineers (IEEE) 1077-2626 1941-0506 Point cloud compression, Shape, Surveys, Three-dimensional displays, Semantics,Task analysis, Surface reconstruction 1 10 2024 2024-10-01 10.1109/tvcg.2023.3344935 http://dx.doi.org/10.1109/tvcg.2023.3344935 COLLEGE NANME COLLEGE CODE Swansea University External research funder(s) paid the OA fee (includes OA grants disbursed by the Library) EPSRC, Royal Society, EP/S021892/1, IEC/NSFC/211159 2024-09-08T17:23:24.2649497 2023-12-18T08:17:35.9377764 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Keneni Tesema 0009-0003-1247-2435 1 Lyndon Hill 0009-0001-9276-2891 2 Mark Jones 0000-0001-8991-1190 3 Muneeb Ahmad 0000-0001-8111-9967 4 Gary Tam 0000-0001-7387-5180 5 65337__29823__3c0bbe3d12124926847f42eae69cbfd9.pdf 65337.VOR.pdf 2024-03-25T11:56:21.7400831 Output 9712869 application/pdf Version of Record true This work is licensed under a Creative Commons Attribution 4.0 License (CC-BY) true eng https://creativecommons.org/licenses/by/4.0/ |
title |
Point Cloud Completion: A Survey |
spellingShingle |
Point Cloud Completion: A Survey Keneni Tesema Mark Jones Muneeb Ahmad Gary Tam |
title_short |
Point Cloud Completion: A Survey |
title_full |
Point Cloud Completion: A Survey |
title_fullStr |
Point Cloud Completion: A Survey |
title_full_unstemmed |
Point Cloud Completion: A Survey |
title_sort |
Point Cloud Completion: A Survey |
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565d5e98f266077e36258ac9c10b2a80 2e1030b6e14fc9debd5d5ae7cc335562 9c42fd947397b1ad2bfa9107457974d5 e75a68e11a20e5f1da94ee6e28ff5e76 |
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565d5e98f266077e36258ac9c10b2a80_***_Keneni Tesema 2e1030b6e14fc9debd5d5ae7cc335562_***_Mark Jones 9c42fd947397b1ad2bfa9107457974d5_***_Muneeb Ahmad e75a68e11a20e5f1da94ee6e28ff5e76_***_Gary Tam |
author |
Keneni Tesema Mark Jones Muneeb Ahmad Gary Tam |
author2 |
Keneni Tesema Lyndon Hill Mark Jones Muneeb Ahmad Gary Tam |
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IEEE Transactions on Visualization and Computer Graphics |
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30 |
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6880 |
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2024 |
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Swansea University |
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1077-2626 1941-0506 |
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10.1109/tvcg.2023.3344935 |
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Institute of Electrical and Electronics Engineers (IEEE) |
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Faculty of Science and Engineering |
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description |
Point cloud completion is the task of producing a complete 3D shape given an input of a partial point cloud. It has become a vital process in 3D computer graphics, vision and applications such as autonomous driving, robotics, and augmented reality. These applications often rely on the presence of a complete 3D representation of the environment. Over the past few years, many completion algorithms have been proposed and a substantial amount of research has been carried out. However, there are not many in-depth surveys that summarise the research progress in such a way that allows users to make an informed choice of what algorithms to employ given the type of data they have, the end result they want, the challenges they may face and the possible strategies they could use. In this study, we present a comprehensive survey and classification of papers on point cloud completion until August 2023 based on the strategies, techniques, inputs, outputs, and network architectures. We will also cover datasets, evaluation methods, and application areas in point cloud completion. Finally, we discuss challenges faced by the research community and future research directions. |
published_date |
2024-10-01T17:23:22Z |
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11.037603 |