{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T19:24:41Z","timestamp":1774121081542,"version":"3.50.1"},"reference-count":58,"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\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2021YFF0901502"],"award-info":[{"award-number":["2021YFF0901502"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61906134"],"award-info":[{"award-number":["61906134"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62020106004"],"award-info":[{"award-number":["62020106004"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["92048301"],"award-info":[{"award-number":["92048301"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61925201"],"award-info":[{"award-number":["61925201"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62132001"],"award-info":[{"award-number":["62132001"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U21B2025"],"award-info":[{"award-number":["U21B2025"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. on Image Process."],"published-print":{"date-parts":[[2022]]},"DOI":"10.1109\/tip.2022.3215024","type":"journal-article","created":{"date-parts":[[2022,11,3]],"date-time":"2022-11-03T22:08:05Z","timestamp":1667513285000},"page":"6831-6846","source":"Crossref","is-referenced-by-count":13,"title":["Dual-View 3D Reconstruction via Learning Correspondence and Dependency of Point Cloud Regions"],"prefix":"10.1109","volume":"31","author":[{"given":"Xin","family":"Jia","sequence":"first","affiliation":[{"name":"Key Laboratory of Computer Vision and System, Ministry of Education, Tianjin University of Technology, Tianjin, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8262-951X","authenticated-orcid":false,"given":"Shourui","family":"Yang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Computer Vision and System, Ministry of Education, Tianjin University of Technology, Tianjin, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6215-8888","authenticated-orcid":false,"given":"Yunbo","family":"Wang","sequence":"additional","affiliation":[{"name":"Wangxuan Institute of Computer Technology, Peking University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7844-6035","authenticated-orcid":false,"given":"Jianhua","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Computer Vision and System, Ministry of Education, Tianjin University of Technology, Tianjin, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7658-3845","authenticated-orcid":false,"given":"Yuxin","family":"Peng","sequence":"additional","affiliation":[{"name":"Wangxuan Institute of Computer Technology, Peking University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6705-3831","authenticated-orcid":false,"given":"Shengyong","family":"Chen","sequence":"additional","affiliation":[{"name":"Key Laboratory of Computer Vision and System, Ministry of Education, Tianjin University of Technology, Tianjin, China"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.01055"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01237-3_47"},{"key":"ref33","first-page":"8293","article-title":"Learning to infer implicit surfaces without 3D supervision","author":"liu","year":"2019","journal-title":"Proc Conf Workshop Neural Inf Process Syst (NeurlPS)"},{"key":"ref32","first-page":"1","article-title":"3D-GMNet: Single-view 3D shape recovery as a Gaussian mixture","author":"yamashita","year":"2020","journal-title":"Proc Brit Mach Vis Conf (BMVC)"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00725"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58586-0_36"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00567"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00609"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00459"},{"key":"ref34","first-page":"1119","article-title":"Scene representation networks: Continuous 3d-structure-aware neural scene representations","author":"sitzmann","year":"2019","journal-title":"Proc Conf Workshop Neural Inf Process Syst (NeurlPS)"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00025"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01224"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00012"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-020-01347-6"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46484-8_38"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58592-1_41"},{"key":"ref22","first-page":"1696","article-title":"Perspective transformer nets: Learning single-view 3D object reconstruction without 3D supervision","author":"yan","year":"2016","journal-title":"Proc Conf Workshop Neural Inf Process Syst (NeurlPS)"},{"key":"ref21","first-page":"1912","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":"ref24","first-page":"2807","article-title":"Unsupervised learning of shape and pose with differentiable point clouds","author":"insafutdinov","year":"2018","journal-title":"Proc Conf Workshop Neural Inf Process Syst (NeurlPS)"},{"key":"ref23","first-page":"216","article-title":"AtlasNet: A Papier–Mâché approach to learning 3D surface generation","author":"groueix","year":"2018","journal-title":"Proc IEEE Conf Comput Vis and Pattern Recog"},{"key":"ref26","first-page":"3994","article-title":"DRWR: A differentiable renderer without rendering for unsupervised 3d structure learning from silhouette images","author":"han","year":"2020","journal-title":"Proc Int Conf Machine Learn (ICML)"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33018819"},{"key":"ref50","article-title":"ShapeNet: An information-rich 3D model repository","author":"chang","year":"2015","journal-title":"arXiv 1512 03012"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00314"},{"key":"ref58","first-page":"55","article-title":"3D-LMNet: Latent embedding matching for accurate and diverse 3D point cloud reconstruction from a single image","author":"mandikal","year":"2018","journal-title":"Proc Brit Mach Vis Conf (BMVC)"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00842"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58595-2_31"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/3DV.2018.00088"},{"key":"ref54","article-title":"PCRNet: Point cloud registration network using PointNet encoding","author":"sarode","year":"2019","journal-title":"arXiv 1908 07906"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00362"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00411"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00298"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/3123266.3123340"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/3DV.2017.00018"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2020.02.001"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00162"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00113"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.2984232"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.264"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/517"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW50498.2020.00141"},{"key":"ref19","first-page":"1","article-title":"Probabilistic reconstruction networks for 3D shape inference from a single image","author":"klokov","year":"2019","journal-title":"Proc Brit Mach Vis Conf (BMVC)"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-019-01217-w"},{"key":"ref3","first-page":"365","article-title":"Learning a multi-view stereo machine","author":"kar","year":"2017","journal-title":"Proc Conf Workshop Neural Inf Process Syst (NeurlPS)"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2021.3073318"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2020.3018865"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2020.2968818"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2021.3082310"},{"key":"ref49","article-title":"Layer normalization","author":"ba","year":"2016","journal-title":"arXiv 1607 06450"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00567"},{"key":"ref46","first-page":"5099","article-title":"PointNet++: Deep hierarchical feature learning on point sets in a metric space","author":"qi","year":"2017","journal-title":"Proc Conf Workshop Neural Inf Process Syst (NeurlPS)"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1007\/s41095-021-0229-5"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00473"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.16"},{"key":"ref42","first-page":"5998","article-title":"Attention is all you need","author":"ashish","year":"2017","journal-title":"Proc Conf Workshop Neural Inf Process Syst (NeurlPS)"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00988"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58452-8_13"},{"key":"ref43","article-title":"An image is worth 16×16 words: Transformers for image recognition at scale","author":"dosovitskiy","year":"2020","journal-title":"arXiv 2010 11929"}],"container-title":["IEEE Transactions on Image Processing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/83\/9626658\/09926975.pdf?arnumber=9926975","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,28]],"date-time":"2022-11-28T19:56:14Z","timestamp":1669665374000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9926975\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"references-count":58,"URL":"https:\/\/doi.org\/10.1109\/tip.2022.3215024","relation":{},"ISSN":["1057-7149","1941-0042"],"issn-type":[{"value":"1057-7149","type":"print"},{"value":"1941-0042","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]}}}