{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T17:33:10Z","timestamp":1777570390878,"version":"3.51.4"},"reference-count":46,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62172021"],"award-info":[{"award-number":["62172021"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62271013"],"award-info":[{"award-number":["62271013"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100017607","name":"Shenzhen Fundamental Research Program","doi-asserted-by":"publisher","award":["GXWD20201231165807007-20200806163656003"],"award-info":[{"award-number":["GXWD20201231165807007-20200806163656003"]}],"id":[{"id":"10.13039\/501100017607","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shenzhen Science and Technology Plan Basic Research Project","award":["JCYJ20190808161805519"],"award-info":[{"award-number":["JCYJ20190808161805519"]}]},{"DOI":"10.13039\/100018919","name":"Major Key Project of Peng Cheng Laboratory","doi-asserted-by":"publisher","award":["PCL2021A06"],"award-info":[{"award-number":["PCL2021A06"]}],"id":[{"id":"10.13039\/100018919","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Geosci. Remote Sensing"],"published-print":{"date-parts":[[2022]]},"DOI":"10.1109\/tgrs.2022.3220198","type":"journal-article","created":{"date-parts":[[2022,11,7]],"date-time":"2022-11-07T22:30:21Z","timestamp":1667860221000},"page":"1-14","source":"Crossref","is-referenced-by-count":9,"title":["QINet: Decision Surface Learning and Adversarial Enhancement for Quasi-Immune Completion of Diverse Corrupted Point Clouds"],"prefix":"10.1109","volume":"60","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4594-3654","authenticated-orcid":false,"given":"Ruonan","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Electronic and Computer Engineering, Peking University Shenzhen Graduate School, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7429-5495","authenticated-orcid":false,"given":"Wei","family":"Gao","sequence":"additional","affiliation":[{"name":"School of Electronic and Computer Engineering, Peking University Shenzhen Graduate School, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0140-0949","authenticated-orcid":false,"given":"Ge","family":"Li","sequence":"additional","affiliation":[{"name":"School of Electronic and Computer Engineering, Peking University Shenzhen Graduate School, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thomas H.","family":"Li","sequence":"additional","affiliation":[{"name":"School of Electronic and Computer Engineering, Peking University Shenzhen Graduate School, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00548"},{"key":"ref38","first-page":"1","article-title":"A learned representation for artistic style","author":"dumoulin","year":"2017","journal-title":"Proc Int Conf Learn Represent"},{"key":"ref33","first-page":"1","article-title":"Continuous control with deep reinforcement learning","author":"lillicrap","year":"2016","journal-title":"Proc IEEE Int Conf Learn Represent"},{"key":"ref32","first-page":"1587","article-title":"Addressing function approximation error in actor-critic methods","author":"fujimoto","year":"2018","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/0921-8890(95)00026-C"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2021.3067096"},{"key":"ref37","first-page":"6594","article-title":"Modulating early visual processing by language","author":"de vries","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00609"},{"key":"ref35","first-page":"1","article-title":"Dynamic graph CNN for learning on point clouds","volume":"38","author":"wang","year":"2019","journal-title":"ACM Trans Graph"},{"key":"ref34","first-page":"2760","article-title":"Model-free imitation learning with policy optimization","author":"ho","year":"2016","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/3394171.3413648"},{"key":"ref40","first-page":"2672","article-title":"Generative adversarial nets","author":"goodfellow","year":"2014","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1084\/jem.52.4.465"},{"key":"ref12","first-page":"135","article-title":"Artificial immunization: Its development and practical use","volume":"28","author":"ellicott","year":"1928","journal-title":"Amer J Nursing"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/37402.37422"},{"key":"ref14","first-page":"5099","article-title":"PointNet++: Deep hierarchical feature learning on point sets in a metric space","author":"qi","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref15","first-page":"192","article-title":"3D ShapeNets: A deep representation for volumetric shapes","author":"wu","year":"2015","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit (CVPR)"},{"key":"ref16","first-page":"40","article-title":"Learning representations and generative models for 3D point clouds","author":"achlioptas","year":"2018","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-018-1126-y"},{"key":"ref18","first-page":"1","article-title":"Unpaired point cloud completion on real scans using adversarial training","author":"chen","year":"2020","journal-title":"Proc Int Conf Learn Represent"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i07.6827"},{"key":"ref28","first-page":"1","article-title":"Energy-based generative adversarial network","author":"zhao","year":"2017","journal-title":"Proc Int Conf Learn Represent"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2022.3145474"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2021.3105551"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2020.2996617"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2015.2408631"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2021.3050551"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2018.2831621"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00168"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/3DV.2018.00088"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2018.2829625"},{"key":"ref9","first-page":"5891","article-title":"RL-GAN-Net: A reinforcement learning agent controlled GAN network for real-time point cloud shape completion","author":"lee","year":"2019","journal-title":"Proc IEEE Conf Comput Vis and Pattern Recog"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.16"},{"key":"ref46","first-page":"61","article-title":"Poisson surface reconstruction","volume":"256","author":"kazhdan","year":"2006","journal-title":"Proc Symp Geometry Process"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00029"},{"key":"ref45","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"van der maaten","year":"2008","journal-title":"J Mach Learn Res"},{"key":"ref22","first-page":"365","article-title":"GRNet: Gridding residual network for dense point cloud completion","author":"xie","year":"2020","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00047"},{"key":"ref42","first-page":"7354","article-title":"Self-attention generative adversarial networks","author":"zhang","year":"2019","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00459"},{"key":"ref41","first-page":"5767","article-title":"Improved training of Wasserstein GANs","author":"gulrajani","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00087"},{"key":"ref44","article-title":"Automatic differentiation in PyTorch","author":"paszke","year":"2017","journal-title":"Proc NIPS Autodiff Workshop Future Gradient-Based Mach Learn Softw Techn"},{"key":"ref26","first-page":"2672","article-title":"Generative adversarial networks","author":"goodfellow","year":"2014","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00352"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2019.00122"}],"container-title":["IEEE Transactions on Geoscience and Remote Sensing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/36\/9633014\/09940924.pdf?arnumber=9940924","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,12]],"date-time":"2022-12-12T19:32:36Z","timestamp":1670873556000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9940924\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"references-count":46,"URL":"https:\/\/doi.org\/10.1109\/tgrs.2022.3220198","relation":{},"ISSN":["0196-2892","1558-0644"],"issn-type":[{"value":"0196-2892","type":"print"},{"value":"1558-0644","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]}}}