{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,22]],"date-time":"2026-01-22T05:43:48Z","timestamp":1769060628905,"version":"3.49.0"},"reference-count":38,"publisher":"IEEE","license":[{"start":{"date-parts":[[2019,6,1]],"date-time":"2019-06-01T00:00:00Z","timestamp":1559347200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,6,1]],"date-time":"2019-06-01T00:00:00Z","timestamp":1559347200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,6]]},"DOI":"10.1109\/cvpr.2019.00113","type":"proceedings-article","created":{"date-parts":[[2020,1,9]],"date-time":"2020-01-09T21:06:13Z","timestamp":1578603973000},"page":"1038-1046","source":"Crossref","is-referenced-by-count":92,"title":["3DN: 3D Deformation Network"],"prefix":"10.1109","author":[{"given":"Weiyue","family":"Wang","sequence":"first","affiliation":[{"name":"USC"}]},{"given":"Duygu","family":"Ceylan","sequence":"additional","affiliation":[{"name":"Adobe Research"}]},{"given":"Radomir","family":"Mech","sequence":"additional","affiliation":[{"name":"Adobe Systems Incorporated"}]},{"given":"Ulrich","family":"Neumann","sequence":"additional","affiliation":[{"name":"USC"}]}],"member":"263","reference":[{"key":"ref38","article-title":"3dprnn: Generating shape primitives with recurrent neural networks","author":"zou","year":"2017","journal-title":"ICCV"},{"key":"ref33","article-title":"Perspective transformer nets: Learning single-view 3d object reconstruction without 3d supervision","author":"yan","year":"2016","journal-title":"NIPS"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1145\/2010324.1964975"},{"key":"ref31","first-page":"1912","article-title":"3d shapenets: A deep representation for volumetric shapes","author":"wu","year":"2015","journal-title":"CVPR"},{"key":"ref30","article-title":"Learning shape priors for single-view 3d completion and reconstruction","author":"wu","year":"2018","journal-title":"NIPS"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.16"},{"key":"ref36","article-title":"Learning semantic deformation flows with 3d convolutional networks","author":"yumer","year":"2016","journal-title":"ECCV"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00029"},{"key":"ref34","article-title":"Learning single-view 3d reconstruction with limited pose supervision","author":"yang","year":"2018","journal-title":"ECCV"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00278"},{"key":"ref11","article-title":"Learning free-form deformations for 3d object reconstruction","author":"jack","year":"2018","journal-title":"ACCV"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1111\/cgf.12838"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00411"},{"key":"ref14","article-title":"Deformnet: Free-form deformation network for 3d shape reconstruction from a single image","author":"kurenkov","year":"2017"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00475"},{"key":"ref16","article-title":"Image2mesh: A learning framework for single image 3d reconstruction","author":"pontes","year":"2017","journal-title":"ACCV"},{"key":"ref17","article-title":"Pointnet: Deep learning on point sets for 3d classification and segmentation","author":"qi","year":"2017","journal-title":"CVPR"},{"key":"ref18","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2014"},{"key":"ref19","article-title":"Surfnet: Generating 3d shape surfaces using deep residual networks","author":"sinha","year":"2018","journal-title":"CVPR"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00272"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/1531326.1531339"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.252"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.264"},{"key":"ref6","article-title":"3d-coded : 3d correspondences by deep deformation","author":"groueix","year":"2018","journal-title":"ECCV"},{"key":"ref29","article-title":"MarrNet: 3D Shape Reconstruction via 2.5D Sketches","author":"wu","year":"2017","journal-title":"NIPS"},{"key":"ref5","article-title":"Learning a predictable and generative vector representation for objects","author":"girdhar","year":"2016","journal-title":"ECCV"},{"key":"ref8","article-title":"Hierarchical surface prediction for 3d object reconstruction","author":"h\u00e4ne","year":"2017","journal-title":"3DV"},{"key":"ref7","article-title":"AtlasNet: A Papier-M&#x00E2;ch&#x00E9; Approach to Learning 3D Surface Generation","author":"groueix","year":"2018","journal-title":"CVPR"},{"key":"ref2","article-title":"3d-r2n2: A unified approach for single and multi-view 3d object reconstruction","author":"choy","year":"2016","journal-title":"ECCV"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/2766890"},{"key":"ref1","article-title":"Shapenet: An information-rich 3d model repository","author":"chang","year":"2015"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/1057432.1057456"},{"key":"ref22","doi-asserted-by":"crossref","DOI":"10.1145\/2816795.2818094","article-title":"Data-driven structural priors for shape completion","author":"sung","year":"2015","journal-title":"ACM Trans on Graphics (Proc of SIGGRAPH)"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00314"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.30"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.230"},{"key":"ref26","article-title":"Adaptive ocnn: A patch-based deep representation of 3d shapes","author":"wang","year":"2018"},{"key":"ref25","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-030-01252-6_4","article-title":"Pixel2mesh: Generating 3d mesh models from single rgb images","author":"wang","year":"2018"}],"event":{"name":"2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","location":"Long Beach, CA, USA","start":{"date-parts":[[2019,6,15]]},"end":{"date-parts":[[2019,6,20]]}},"container-title":["2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8938205\/8953184\/08954215.pdf?arnumber=8954215","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,21]],"date-time":"2025-08-21T18:22:50Z","timestamp":1755800570000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8954215\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,6]]},"references-count":38,"URL":"https:\/\/doi.org\/10.1109\/cvpr.2019.00113","relation":{},"subject":[],"published":{"date-parts":[[2019,6]]}}}