{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T19:27:45Z","timestamp":1769542065537,"version":"3.49.0"},"reference-count":28,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Natural Key R&D Program of China","award":["2023YFF0905000"],"award-info":[{"award-number":["2023YFF0905000"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Signal Process. Lett."],"published-print":{"date-parts":[[2026]]},"DOI":"10.1109\/lsp.2026.3653693","type":"journal-article","created":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T21:02:08Z","timestamp":1768338128000},"page":"648-652","source":"Crossref","is-referenced-by-count":0,"title":["Robust Watermarking for 3D Mesh Models Based on Geometrically Weighted Aggregation"],"prefix":"10.1109","volume":"33","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8053-4587","authenticated-orcid":false,"given":"Fei","family":"Peng","sequence":"first","affiliation":[{"name":"School of Artificial Intelligence, and Guangdong Key Laboratory of Blockchain Security, Guangzhou University, Guangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhanhong","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, and Guangdong Key Laboratory of Blockchain Security, Guangzhou University, Guangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1229-2317","authenticated-orcid":false,"given":"Min","family":"Long","sequence":"additional","affiliation":[{"name":"School of Electronics and Communication Engineering, Guangzhou University, Guangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"issue":"6","key":"ref1","first-page":"14","article-title":"A survey of digital watermarking for 3 D geometric models","volume":"24","author":"Liu","year":"2007","journal-title":"Comput. Appl. Softw."},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-10-4154-9_37"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2019.8683753"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2022.3192542"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2023.3295578"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2021.3052468"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2020.3009492"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TrustCom63139.2024.00033"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1186\/s42400-022-00125-w"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i7.28613"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00979"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539463"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/3506694"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/3326362"},{"key":"ref15","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":"ref16","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.","volume":"30","author":"Qi","year":"2017"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00985"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2019.2935152"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/WACV51458.2022.00242"},{"key":"ref20","first-page":"1","article-title":"Graph attention networks","volume-title":"Proc. 6th Int. Conf. Learn. Representations","author":"Velikovi","year":"2018"},{"key":"ref21","article-title":"GTNet: Graph transformer network for 3D point cloud classification and semantic segmentation","author":"Zhou","year":"2024"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01595"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/VISUAL.1998.745314"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298801"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01146"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/3130800.3130883"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.261"},{"key":"ref28","article-title":"ShapeNet: An information-rich 3D model repository","author":"Chang","year":"2015"}],"container-title":["IEEE Signal Processing Letters"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/97\/11304147\/11347573.pdf?arnumber=11347573","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T06:10:57Z","timestamp":1769494257000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11347573\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":28,"URL":"https:\/\/doi.org\/10.1109\/lsp.2026.3653693","relation":{},"ISSN":["1070-9908","1558-2361"],"issn-type":[{"value":"1070-9908","type":"print"},{"value":"1558-2361","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]}}}