{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,23]],"date-time":"2026-04-23T11:11:41Z","timestamp":1776942701554,"version":"3.51.4"},"reference-count":40,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2024,11,18]],"date-time":"2024-11-18T00:00:00Z","timestamp":1731888000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,11,18]],"date-time":"2024-11-18T00:00:00Z","timestamp":1731888000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Front. Comput. Sci."],"published-print":{"date-parts":[[2025,2]]},"DOI":"10.1007\/s11704-023-3455-4","type":"journal-article","created":{"date-parts":[[2024,11,18]],"date-time":"2024-11-18T07:29:16Z","timestamp":1731914956000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["FPSMix: data augmentation strategy for point cloud classification"],"prefix":"10.1007","volume":"19","author":[{"given":"Taiyan","family":"Chen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xianghua","family":"Ying","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,11,18]]},"reference":[{"key":"3455_CR1","first-page":"77","volume-title":"Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","author":"C R Qi","year":"2017","unstructured":"Qi C R, Hao S, Mo K, Guibas L J. PointNet: deep learning on point sets for 3D classification and segmentation. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. 2017, 77\u201385"},{"key":"3455_CR2","first-page":"5105","volume-title":"Proceedings of the 31st International Conference on Neural Information Processing Systems","author":"C R Qi","year":"2017","unstructured":"Qi C R, Li Y, Hao S, Guibas L J. PointNet++: deep hierarchical feature learning on point sets in a metric space. In: Proceedings of the 31st International Conference on Neural Information Processing Systems. 2017, 5105\u20135114"},{"issue":"5","key":"3455_CR3","doi-asserted-by":"publisher","first-page":"146","DOI":"10.1145\/3326362","volume":"38","author":"Y Wang","year":"2019","unstructured":"Wang Y, Sun Y, Liu Z, Sarma S E, Bronstein M M, Solomon J M. Dynamic graph CNN for learning on point clouds. ACM Transactions on Graphics, 2019, 38(5): 146","journal-title":"ACM Transactions on Graphics"},{"key":"3455_CR4","first-page":"8887","volume-title":"Proceedings of IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Y Liu","year":"2019","unstructured":"Liu Y, Fan B, Xiang S, Pan C. Relation-shape convolutional neural network for point cloud analysis. In: Proceedings of IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 2019, 8887\u20138896"},{"key":"3455_CR5","first-page":"6410","volume-title":"Proceedings of IEEE\/CVF International Conference on Computer Vision","author":"H Thomas","year":"2019","unstructured":"Thomas H, Qi C R, Deschaud J E, Marcotegui B, Goulette F, Guibas L. KPConv: flexible and deformable convolution for point clouds. In: Proceedings of IEEE\/CVF International Conference on Computer Vision. 2019, 6410\u20136419"},{"key":"3455_CR6","first-page":"248","volume-title":"Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","author":"J Deng","year":"2009","unstructured":"Deng J, Dong W, Socher R, Li L J, Li K, Fei-Fei L. ImageNet: a large-scale hierarchical image database. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. 2009, 248\u2013255"},{"key":"3455_CR7","first-page":"1912","volume-title":"Proceedings of IEEE Conference on Computer Vision and Pattern Recognition","author":"Z Wu","year":"2015","unstructured":"Wu Z, Song S, Khosla A, Yu F, Zhang L, Tang X, Xiao J. 3D ShapeNets: a deep representation for volumetric shapes. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. 2015, 1912\u20131920"},{"key":"3455_CR8","first-page":"6377","volume-title":"Proceedings of IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"R Li","year":"2020","unstructured":"Li R, Li X, Heng P A, Fu C W. PointAugment: an auto-augmentation framework for point cloud classification. In: Proceedings of IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 2020, 6377\u20136386"},{"key":"3455_CR9","volume-title":"Proceedings of the 6th International Conference on Learning Representations","author":"H Zhang","year":"2018","unstructured":"Zhang H, Cisse M, Dauphin Y N, Lopez-Paz D. mixup: beyond empirical risk minimization. In: Proceedings of the 6th International Conference on Learning Representations. 2018"},{"key":"3455_CR10","first-page":"6022","volume-title":"Proceedings of IEEE\/CVF International Conference on Computer Vision","author":"S Yun","year":"2019","unstructured":"Yun S, Han D, Chun S, Oh S J, Yoo Y, Choe J. CutMix: regularization strategy to train strong classifiers with localizable features. In: Proceedings of IEEE\/CVF International Conference on Computer Vision. 2019, 6022\u20136031"},{"key":"3455_CR11","first-page":"15895","volume-title":"Proceedings of IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"D Lee","year":"2021","unstructured":"Lee D, Lee J, Lee J, Lee H, Lee M, Woo S, Lee S. Regularization strategy for point cloud via rigidly mixed sample. In: Proceedings of IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 2021, 15895\u201315904"},{"key":"3455_CR12","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1016\/j.neucom.2022.07.049","volume":"505","author":"J Zhang","year":"2022","unstructured":"Zhang J, Chen L, Ouyang B, Liu B, Zhu J, Chen Y, Meng Y, Wu D. PointCutMix: regularization strategy for point cloud classification. Neurocomputing, 2022, 505: 58\u201367","journal-title":"Neurocomputing"},{"key":"3455_CR13","first-page":"330","volume-title":"Proceedings of the 16th European Conference on Computer Vision","author":"Y Chen","year":"2020","unstructured":"Chen Y, Hu V T, Gavves E, Mensink T, Mettes P, Yang P, Snoek C G M. PointMixup: augmentation for point clouds. In: Proceedings of the 16th European Conference on Computer Vision. 2020, 330\u2013345"},{"key":"3455_CR14","first-page":"202","volume-title":"Proceedings of the 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention","author":"Z Ding","year":"2019","unstructured":"Ding Z, Han X, Niethammer M. VoteNet: a deep learning label fusion method for multi-atlas segmentation. In: Proceedings of the 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention. 2019, 202\u2013210"},{"key":"3455_CR15","first-page":"11629","volume-title":"Proceedings of IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Y He","year":"2020","unstructured":"He Y, Sun W, Huang H, Liu J, Fan H, Sun J. PVN3D: a deep point-wise 3D keypoints voting network for 6DoF pose estimation. In: Proceedings of IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 2020, 11629\u201311638"},{"key":"3455_CR16","first-page":"9397","volume-title":"Proceedings of IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"J Li","year":"2018","unstructured":"Li J, Chen B M, Lee G H. SO-Net: self-organizing network for point cloud analysis. In: Proceedings of IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 2018, 9397\u20139406"},{"key":"3455_CR17","first-page":"828","volume-title":"Proceedings of the 32nd International Conference on Neural Information Processing Systems","author":"Y Li","year":"2018","unstructured":"Li Y, Bu R, Sun M, Wu W, Di X, Chen B. PointCNN: convolution on X-transformed points. In: Proceedings of the 32nd International Conference on Neural Information Processing Systems. 2018, 828\u2013838"},{"key":"3455_CR18","first-page":"90","volume-title":"Proceedings of the 15th European Conference on Computer Vision","author":"Y Xu","year":"2018","unstructured":"Xu Y, Fan T, Xu M, Zeng L, Qiao Y. SpiderCNN: deep learning on point sets with parameterized convolutional filters. In: Proceedings of the 15th European Conference on Computer Vision. 2018, 90\u2013105"},{"key":"3455_CR19","first-page":"5238","volume-title":"Proceedings of IEEE\/CVF International Conference on Computer Vision","author":"Y Liu","year":"2019","unstructured":"Liu Y, Fan B, Meng G, Lu J, Xiang S, Pan C. DensePoint: learning densely contextual representation for efficient point cloud processing. In: Proceedings of IEEE\/CVF International Conference on Computer Vision. 2019, 5238\u20135247"},{"key":"3455_CR20","first-page":"56","volume-title":"Proceedings of the 15th European Conference on Computer Vision","author":"C Wang","year":"2018","unstructured":"Wang C, Samari B, Siddiqi K. Local spectral graph convolution for point set feature learning. In: Proceedings of the 15th European Conference on Computer Vision. 2018, 56\u201371"},{"key":"3455_CR21","first-page":"4548","volume-title":"Proceedings of IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Y Shen","year":"2018","unstructured":"Shen Y, Feng C, Yang Y, Tian D. Mining point cloud local structures by kernel correlation and graph pooling. In: Proceedings of IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 2018, 4548\u20134557"},{"key":"3455_CR22","first-page":"7545","volume-title":"Proceedings of IEEE\/CVF International Conference on Computer Vision","author":"J Liu","year":"2019","unstructured":"Liu J, Ni B, Li C, Yang J, Tian Q. Dynamic points agglomeration for hierarchical point sets learning. In: Proceedings of IEEE\/CVF International Conference on Computer Vision. 2019, 7545\u20137554"},{"key":"3455_CR23","first-page":"2530","volume-title":"Proceedings of IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"H Su","year":"2018","unstructured":"Su H, Jampani V, Sun D, Maji S, Kalogerakis E, Yang M H, Kautz J. SPLATNet: sparse lattice networks for point cloud processing. In: Proceedings of IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 2018, 2530\u20132539"},{"key":"3455_CR24","first-page":"9613","volume-title":"Proceedings of IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"W Wu","year":"2019","unstructured":"Wu W, Qi Z, Fuxin L. PointConv: deep convolutional networks on 3D point clouds. In: Proceedings of IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 2019, 9613\u20139622"},{"key":"3455_CR25","first-page":"1578","volume-title":"Proceedings of IEEE\/CVF International Conference on Computer Vision","author":"J Mao","year":"2019","unstructured":"Mao J, Wang X, Li H. Interpolated convolutional networks for 3D point cloud understanding. In: Proceedings of IEEE\/CVF International Conference on Computer Vision. 2019, 1578\u20131587"},{"key":"3455_CR26","first-page":"3172","volume-title":"Proceedings of IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"M Xu","year":"2021","unstructured":"Xu M, Ding R, Zhao H, Qi X. PAConv: position adaptive convolution with dynamic kernel assembling on point clouds. In: Proceedings of IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 2021, 3172\u20133181"},{"issue":"1","key":"3455_CR27","doi-asserted-by":"publisher","first-page":"161301","DOI":"10.1007\/s11704-020-9521-2","volume":"16","author":"H Wang","year":"2022","unstructured":"Wang H, Huang D, Wang Y. GridNet: efficiently learning deep hierarchical representation for 3D point cloud understanding. Frontiers of Computer Science, 2022, 16(1): 161301","journal-title":"Frontiers of Computer Science"},{"key":"3455_CR28","first-page":"895","volume-title":"Proceedings of IEEE\/CVF International Conference on Computer Vision","author":"T Xiang","year":"2021","unstructured":"Xiang T, Zhang C, Song Y, Yu J, Cai W. Walk in the cloud: learning curves for point clouds shape analysis. In: Proceedings of IEEE\/CVF International Conference on Computer Vision. 2021, 895\u2013904"},{"issue":"2","key":"3455_CR29","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1007\/s41095-021-0229-5","volume":"7","author":"M H Guo","year":"2021","unstructured":"Guo M H, Cai J X, Liu Z N, Mu T J, Martin R R, Hu S M. PCT: point cloud transformer. Computational Visual Media, 2021, 7(2): 187\u2013199","journal-title":"Computational Visual Media"},{"key":"3455_CR30","first-page":"16239","volume-title":"Proceedings of IEEE\/CVF International Conference on Computer Vision","author":"H Zhao","year":"2021","unstructured":"Zhao H, Jiang L, Jia J, Torr P, Koltun V. Point transformer. In: Proceedings of IEEE\/CVF International Conference on Computer Vision. 2021, 16239\u201316248"},{"issue":"6","key":"3455_CR31","doi-asserted-by":"publisher","first-page":"176708","DOI":"10.1007\/s11704-022-2435-4","volume":"17","author":"S Liu","year":"2023","unstructured":"Liu S, Luo X, Fu K, Wang M, Song Z. A learnable self-supervised task for unsupervised domain adaptation on point cloud classification and segmentation. Frontiers of Computer Science, 2023, 17(6): 176708","journal-title":"Frontiers of Computer Science"},{"issue":"1","key":"3455_CR32","doi-asserted-by":"publisher","first-page":"170","DOI":"10.1007\/s11704-016-6191-1","volume":"13","author":"Y Xian","year":"2019","unstructured":"Xian Y, Xiao J, Wang Y. A fast registration algorithm of rock point cloud based on spherical projection and feature extraction. Frontiers of Computer Science, 2019, 13(1): 170\u2013182","journal-title":"Frontiers of Computer Science"},{"issue":"3","key":"3455_CR33","doi-asserted-by":"publisher","first-page":"402","DOI":"10.1007\/s11704-014-3413-2","volume":"9","author":"H Li","year":"2015","unstructured":"Li H, Liu Y, Xiong S, Wang L. Pedestrian detection algorithm based on video sequences and laser point cloud. Frontiers of Computer Science, 2015, 9(3): 402\u2013414","journal-title":"Frontiers of Computer Science"},{"key":"3455_CR34","first-page":"13789","volume-title":"Proceedings of IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"A Dabouei","year":"2021","unstructured":"Dabouei A, Soleymani S, Taherkhani F, Nasrabadi N M. SuperMix: supervising the mixing data augmentation. In: Proceedings of IEEE\/CVF Conference on Computer Vision and Pattern Recognition. 2021, 13789\u201313798"},{"key":"3455_CR35","first-page":"6438","volume-title":"Proceedings of the 36th International Conference on Machine Learning","author":"V Verma","year":"2019","unstructured":"Verma V, Lamb A, Beckham C, Najafi A, Mitliagkas I, Lopez-Paz D, Bengio Y. Manifold mixup: better representations by interpolating hidden states. In: Proceedings of the 36th International Conference on Machine Learning. 2019, 6438\u20136447"},{"key":"3455_CR36","first-page":"3714","volume-title":"Proceedings of the 33rd AAAI Conference on Artificial Intelligence","author":"H Guo","year":"2019","unstructured":"Guo H, Mao Y, Zhang R. MixUp as locally linear out-of-manifold regularization. In: Proceedings of the 33rd AAAI Conference on Artificial Intelligence. 2019, 3714\u20133722"},{"key":"3455_CR37","unstructured":"Harris E, Marcu A, Painter M, Niranjan M, Pr\u00fcgel-Bennett A, Hare J. FMix: enhancing mixed sample data augmentation. 2020, arXiv preprint arXiv: 2002.12047"},{"key":"3455_CR38","volume-title":"Proceedings of the 31st Conference on Neural Information Processing Systems","author":"A Paszke","year":"2017","unstructured":"Paszke A, Gross S, Chintala S, Chanan G, Yang E, DeVito Z, Lin Z, Desmaison A, Antiga L, Lerer A. Automatic differentiation in PyTorch. In: Proceedings of the 31st Conference on Neural Information Processing Systems. 2017"},{"key":"3455_CR39","volume-title":"Proceedings of the 3rd International Conference on Learning Representations","author":"D P Kingma","year":"2015","unstructured":"Kingma D P, Ba J. Adam: a method for stochastic optimization. In: Proceedings of the 3rd International Conference on Learning Representations. 2015"},{"key":"3455_CR40","volume-title":"Proceedings of the 5th International Conference on Learning Representations","author":"I Loshchilov","year":"2017","unstructured":"Loshchilov I, Hutter F. SGDR: stochastic gradient descent with warm restarts. In: Proceedings of the 5th International Conference on Learning Representations. 2017"}],"container-title":["Frontiers of Computer Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11704-023-3455-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11704-023-3455-4","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11704-023-3455-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,22]],"date-time":"2026-03-22T20:28:06Z","timestamp":1774211286000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11704-023-3455-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,18]]},"references-count":40,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2025,2]]}},"alternative-id":["3455"],"URL":"https:\/\/doi.org\/10.1007\/s11704-023-3455-4","relation":{},"ISSN":["2095-2228","2095-2236"],"issn-type":[{"value":"2095-2228","type":"print"},{"value":"2095-2236","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,11,18]]},"assertion":[{"value":"3 June 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 November 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 November 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Competing interests\n                      The authors declare that they have no competing interests or financial conflicts to disclose.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics"}}],"article-number":"192701"}}