{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T09:18:39Z","timestamp":1774430319180,"version":"3.50.1"},"reference-count":49,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Tianshan Yingcai Peiyang 2023","award":["TSYCLJ0023"],"award-info":[{"award-number":["TSYCLJ0023"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62373343"],"award-info":[{"award-number":["62373343"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004826","name":"Beijing Natural Science Foundation","doi-asserted-by":"publisher","award":["L233036"],"award-info":[{"award-number":["L233036"]}],"id":[{"id":"10.13039\/501100004826","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Brazilian National Council for Scientific and Technological Development - CNPq","award":["306607\/2023-9"],"award-info":[{"award-number":["306607\/2023-9"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Multimedia"],"published-print":{"date-parts":[[2024]]},"DOI":"10.1109\/tmm.2024.3374580","type":"journal-article","created":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T18:49:08Z","timestamp":1710269348000},"page":"8052-8062","source":"Crossref","is-referenced-by-count":50,"title":["PointGT: A Method for Point-Cloud Classification and Segmentation Based on Local Geometric Transformation"],"prefix":"10.1109","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-9229-7181","authenticated-orcid":false,"given":"Huang","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Software, Xinjiang University, Xinjiang, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4056-4922","authenticated-orcid":false,"given":"Changshuo","family":"Wang","sequence":"additional","affiliation":[{"name":"Cyber Security Research Centre, Nanyang Technological University, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9041-0801","authenticated-orcid":false,"given":"Long","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Software, Xinjiang University, Xinjiang, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3525-5102","authenticated-orcid":false,"given":"Shengwei","family":"Tian","sequence":"additional","affiliation":[{"name":"School of Software, Xinjiang University, Xinjiang, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7897-1673","authenticated-orcid":false,"given":"Xin","family":"Ning","sequence":"additional","affiliation":[{"name":"Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8657-3800","authenticated-orcid":false,"given":"Joel","family":"Rodrigues","sequence":"additional","affiliation":[{"name":"Amazonas State University, Manaus, Brazil"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/tmm.2022.3146714"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2022.3216951"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2022.3170493"},{"key":"ref4","first-page":"282","article-title":"Conditional random fields: Probabilistic models for segmenting and labeling sequence data","volume-title":"Proc. 18th Int. Conf. Mach. Learn.","author":"Lafferty","year":"2001"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr.2009.5206590"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.displa.2023.102456"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.33851\/JMIS.2022.9.3.183"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2023.110422"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/tmm.2022.3183388"},{"key":"ref10","first-page":"652","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":"ref11","first-page":"5105","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":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00571"},{"key":"ref13","article-title":"Rethinking network design and local geometry in point cloud: A simple residual MLP framework","author":"Ma","year":"2021","journal-title":"Int. Conf. Learn. Representations"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/jas.2023.123432"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01837"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00651"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00563"},{"key":"ref18","first-page":"23580","article-title":"SageMix: Saliency-guided mixup for point clouds","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Lee","year":"2022"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00641"},{"key":"ref20","first-page":"828","article-title":"PointCNN: Convolution on X-transformed points","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Li","year":"2018"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00985"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1145\/3326362"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01595"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/s41095-021-0229-5"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2020.107446"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2021.3074240"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr42600.2020.01112"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00831"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2018.2820126"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2014.2329213"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298801"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.99"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00979"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33018778"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00435"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00166"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/icpr56361.2022.9956172"},{"key":"ref39","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":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00167"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01237-3_6"},{"key":"ref42","first-page":"3809","article-title":"Revisiting point cloud shape classification with a simple and effective baseline","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Goyal","year":"2021"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/WACV48630.2021.00386"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2021.3072214"},{"key":"ref45","first-page":"32398","article-title":"Let images give you more: Point cloud cross-modal training for shape analysis","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Yan","year":"2022"},{"key":"ref46","article-title":"ShapeNet: An information-rich 3D model repository","author":"Chang","year":"2015"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1145\/3197517.3201301"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00910"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr52688.2022.01871"}],"container-title":["IEEE Transactions on Multimedia"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6046\/10384483\/10462543.pdf?arnumber=10462543","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,2]],"date-time":"2024-08-02T04:48:21Z","timestamp":1722574101000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10462543\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":49,"URL":"https:\/\/doi.org\/10.1109\/tmm.2024.3374580","relation":{},"ISSN":["1520-9210","1941-0077"],"issn-type":[{"value":"1520-9210","type":"print"},{"value":"1941-0077","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]}}}