{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,9]],"date-time":"2025-12-09T08:27:23Z","timestamp":1765268843008,"version":"build-2065373602"},"reference-count":37,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2022,8,26]],"date-time":"2022-08-26T00:00:00Z","timestamp":1661472000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61906140","2020CFA063","T2021009"],"award-info":[{"award-number":["61906140","2020CFA063","T2021009"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the Hubei Province Natural Science Foundation for Distinguished Young Scholars","award":["61906140","2020CFA063","T2021009"],"award-info":[{"award-number":["61906140","2020CFA063","T2021009"]}]},{"name":"the Excellent young and middle-aged scientific and technological innovation teams in colleges and universities of Hubei Province","award":["61906140","2020CFA063","T2021009"],"award-info":[{"award-number":["61906140","2020CFA063","T2021009"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>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 \u201csimple\u201d network, such as multilayer perceptrons (MLPs), to generate a coarse point cloud and then a \u201ccomplex\u201d network, such as auto-encoders or transformers, to enhance local details. It can directly learn the mapping between missing and complete points, ensuring that the structure of the input missing point cloud remains unchanged while accurately predicting the complete points. This approach follows the minimalist design of U-Net. In the encoder, we encode the point clouds into point cloud blocks by iterative farthest point sampling (IFPS) and k-nearest neighbors and then extract the depth interaction features between the missing point cloud blocks by the attention mechanism. In the decoder, we introduce a new trilinear interpolation method to recover point cloud details, with the help of the coordinate space and feature space of low-resolution point clouds, and missing point cloud information. This paper also proposes a method to generate multi-view missing point cloud data using a 3D point cloud hidden point removal algorithm, so that each 3D point cloud model generates a missing point cloud through eight uniformly distributed camera poses. Experiments validate the effectiveness and superiority of PCA-Net in several challenging point cloud completion tasks, and PCA-Net also shows great versatility and robustness in real-world missing point cloud completion.<\/jats:p>","DOI":"10.3390\/s22176439","type":"journal-article","created":{"date-parts":[[2022,8,30]],"date-time":"2022-08-30T01:37:55Z","timestamp":1661823475000},"page":"6439","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["End-to-End Point Cloud Completion Network with Attention Mechanism"],"prefix":"10.3390","volume":"22","author":[{"given":"Yaqin","family":"Li","sequence":"first","affiliation":[{"name":"School of Mathematics and Computer Science, Wuhan Polytechnic University, Wuhan 430024, China"}]},{"given":"Binbin","family":"Han","sequence":"additional","affiliation":[{"name":"School of Mathematics and Computer Science, Wuhan Polytechnic University, Wuhan 430024, China"}]},{"given":"Shan","family":"Zeng","sequence":"additional","affiliation":[{"name":"School of Mathematics and Computer Science, Wuhan Polytechnic University, Wuhan 430024, China"}]},{"given":"Shengyong","family":"Xu","sequence":"additional","affiliation":[{"name":"College of Engineering, Huazhong Agricultural University, Wuhan 430070, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8775-0626","authenticated-orcid":false,"given":"Cao","family":"Yuan","sequence":"additional","affiliation":[{"name":"School of Mathematics and Computer Science, Wuhan Polytechnic University, Wuhan 430024, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,8,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Yu, T., Meng, J., and Yuan, J. 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