{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,12]],"date-time":"2025-06-12T18:10:09Z","timestamp":1749751809590,"version":"3.41.0"},"reference-count":44,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"7","license":[{"start":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T00:00:00Z","timestamp":1751328000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T00:00:00Z","timestamp":1751328000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T00:00:00Z","timestamp":1751328000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62125305"],"award-info":[{"award-number":["62125305"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Nature Science Basic Research Plan in Shaanxi Province of China","award":["2025JC-JCQN-091"],"award-info":[{"award-number":["2025JC-JCQN-091"]}]},{"name":"Shaanxi Province Technology Innovation Guidance Special Project","award":["2024QY-SZx-23"],"award-info":[{"award-number":["2024QY-SZx-23"]}]},{"name":"Applied Technology Research and Development Project in Beilin District, Xi'an City","award":["GX2305"],"award-info":[{"award-number":["GX2305"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Robot. Autom. Lett."],"published-print":{"date-parts":[[2025,7]]},"DOI":"10.1109\/lra.2025.3575996","type":"journal-article","created":{"date-parts":[[2025,6,2]],"date-time":"2025-06-02T18:03:20Z","timestamp":1748887400000},"page":"7388-7395","source":"Crossref","is-referenced-by-count":0,"title":["PointFM: Point Cloud Understanding by Flow Matching"],"prefix":"10.1109","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8723-9924","authenticated-orcid":false,"given":"Haozhe","family":"Cheng","sequence":"first","affiliation":[{"name":"School of Software Engineering, Xi'an Jiaotong University, Xi'an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lintong","family":"Wei","sequence":"additional","affiliation":[{"name":"School of Electronics and Information, Xi'an Polytechnic University, Xi'an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-6617-4704","authenticated-orcid":false,"given":"Wenjing","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Electronics and Information, Xi'an Polytechnic University, Xi'an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jian","family":"Lu","sequence":"additional","affiliation":[{"name":"School of Electronics and Information, Xi'an Polytechnic University, Xi'an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiahua","family":"Xiao","sequence":"additional","affiliation":[{"name":"School of Software Engineering, Xi'an Jiaotong University, Xi'an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3081-8781","authenticated-orcid":false,"given":"Jihua","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Software Engineering, Xi'an Jiaotong University, Xi'an, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1810.04805"},{"key":"ref3","first-page":"309","article-title":"Predicting what you already know helps: Provable self-supervised learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Lee","year":"2021"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2022.3142440"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01553"},{"key":"ref6","first-page":"6840","article-title":"Denoising diffusion probabilistic models","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Ho","year":"2020"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00286"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.02164"},{"key":"ref9","first-page":"1","article-title":"Flow matching for generative modeling","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Lipman","year":"2023"},{"key":"ref10","first-page":"6572","article-title":"Neural ordinary differential equations","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Chen","year":"2018"},{"article-title":"Flow matching in latent space","year":"2023","author":"Dao","key":"ref11"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2024.3430904"},{"key":"ref13","first-page":"1","article-title":"Density estimation using real NVP","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Dinh","year":"2017"},{"key":"ref14","first-page":"10021","article-title":"Lion: Latent point diffusion models for 3D shape generation","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Vahdat","year":"2022"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01871"},{"key":"ref16","first-page":"1","article-title":"Discrete variational autoencoders","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Rolfe","year":"2017"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-20086-1_35"},{"key":"ref18","first-page":"32653","article-title":"PointMamba: A simple state space model for point cloud analysis","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Liang","year":"2024"},{"key":"ref19","first-page":"1","article-title":"Flow straight and fast: Learning to generate and transfer data with rectified flow","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Liu","year":"2023"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i7.28522"},{"article-title":"ShapeNet: An information-rich 3D model repository","year":"2015","author":"Chang","key":"ref21"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00290"},{"key":"ref23","first-page":"23192","article-title":"PointNext: Revisiting pointnet with improved training and scaling strategies","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Qian","year":"2022"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00167"},{"key":"ref25","first-page":"77","article-title":"PointNet: Deep learning on point sets for 3D classification and segmentation","volume-title":"Proc. IEEE Conf. Comput. Vis. Pattern Recognit.","author":"Qi","year":"2017"},{"key":"ref26","first-page":"1","article-title":"PointNet : Deep hierarchical feature learning on point sets in a metric space","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Qi","year":"2017"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/3326362"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-20086-1_38"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00519"},{"key":"ref31","first-page":"1","article-title":"Autoencoders as cross-modal teachers: Can pretrained 2D image transformers help 3D representation learning?","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Dong","year":"2023"},{"key":"ref32","first-page":"27061","article-title":"Point-M2AE: Multi-scale masked autoencoders for hierarchical point cloud pre-training","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Zhang","year":"2022"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2022.3224370"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298801"},{"key":"ref35","first-page":"1","article-title":"Self-supervised deep learning on point clouds by reconstructing space","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Sauder","year":"2019"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2023\/88"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2022.3147907"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.261"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58580-8_34"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01009"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00647"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00327"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.170"},{"key":"ref44","first-page":"80303","article-title":"PCP-MAE: Learning to predict centers for point masked autoencoders","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Zhang","year":"2025"}],"container-title":["IEEE Robotics and Automation Letters"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/7083369\/11008675\/11021383.pdf?arnumber=11021383","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,12]],"date-time":"2025-06-12T17:44:55Z","timestamp":1749750295000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11021383\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7]]},"references-count":44,"journal-issue":{"issue":"7"},"URL":"https:\/\/doi.org\/10.1109\/lra.2025.3575996","relation":{},"ISSN":["2377-3766","2377-3774"],"issn-type":[{"type":"electronic","value":"2377-3766"},{"type":"electronic","value":"2377-3774"}],"subject":[],"published":{"date-parts":[[2025,7]]}}}