{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T11:30:44Z","timestamp":1757590244823,"version":"3.41.2"},"reference-count":27,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2021,4,27]],"date-time":"2021-04-27T00:00:00Z","timestamp":1619481600000},"content-version":"vor","delay-in-days":116,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100007421","name":"Li Ka Shing Foundation","doi-asserted-by":"publisher","award":["2020LKSFG04D","2020LKSFG05D"],"award-info":[{"award-number":["2020LKSFG04D","2020LKSFG05D"]}],"id":[{"id":"10.13039\/100007421","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["2019A1515010943","S2018A030313420","2021A1515012302"],"award-info":[{"award-number":["2019A1515010943","S2018A030313420","2021A1515012302"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100009047","name":"Shantou University","doi-asserted-by":"publisher","award":["09420021"],"award-info":[{"award-number":["09420021"]}],"id":[{"id":"10.13039\/100009047","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004607","name":"Natural Science Foundation of Guangxi Province","doi-asserted-by":"publisher","award":["2018GXNSFAA294127"],"award-info":[{"award-number":["2018GXNSFAA294127"]}],"id":[{"id":"10.13039\/501100004607","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61902232","61902087"],"award-info":[{"award-number":["61902232","61902087"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Wireless Communications and Mobile Computing"],"published-print":{"date-parts":[[2021,1]]},"abstract":"<jats:p>In this paper, we introduce a novel 3D shape reconstruction method from a single\u2010view sketch image based on a deep neural network. The proposed pipeline is mainly composed of three modules. The first module is sketch component segmentation based on multimodal DNN fusion and is used to segment a given sketch into a series of basic units and build a transformation template by the knots between them. The second module is a nonlinear transformation network for multifarious sketch generation with the obtained transformation template. It creates the transformation representation of a sketch by extracting the shape features of an input sketch and transformation template samples. The third module is deep 3D shape reconstruction using multifarious sketches, which takes the obtained sketches as input to reconstruct 3D shapes with a generative model. It fuses and optimizes features of multiple views and thus is more likely to generate high\u2010quality 3D shapes. To evaluate the effectiveness of the proposed method, we conduct extensive experiments on a public 3D reconstruction dataset. The results demonstrate that our model can achieve better reconstruction performance than peer methods. Specifically, compared to the state\u2010of\u2010the\u2010art method, the proposed model achieves a performance gain in terms of the five evaluation metrics by an average of 25.5% on the man\u2010made model dataset and 23.4% on the character object dataset using synthetic sketches and by an average of 31.8% and 29.5% on the two datasets, respectively, using human drawing sketches.<\/jats:p>","DOI":"10.1155\/2021\/5577530","type":"journal-article","created":{"date-parts":[[2021,4,27]],"date-time":"2021-04-27T21:35:26Z","timestamp":1619559326000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Reconstructing 3D Model from Single\u2010View Sketch with Deep Neural Network"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8949-1894","authenticated-orcid":false,"given":"Fei","family":"Wang","sequence":"first","affiliation":[]},{"given":"Yu","family":"Yang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0574-1663","authenticated-orcid":false,"given":"Baoquan","family":"Zhao","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0781-9126","authenticated-orcid":false,"given":"Dazhi","family":"Jiang","sequence":"additional","affiliation":[]},{"given":"Siwei","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Jianqiang","family":"Sheng","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2021,4,27]]},"reference":[{"key":"e_1_2_9_1_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2185520.2185540","article-title":"How do humans sketch objects?","volume":"31","author":"Eitz M.","year":"2012","journal-title":"Acm Transactions on Graphics"},{"key":"e_1_2_9_2_2","doi-asserted-by":"crossref","unstructured":"WangF. YuY. ZhaoB. JiangJ. ZhouT. JiangD. andCaiT. Deep 3D shape reconstruction from single-view sketch image The 8th International Conference on Digital Home 2020 Dalian China.","DOI":"10.1109\/ICDH51081.2020.00039"},{"key":"e_1_2_9_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2020.08.033"},{"key":"e_1_2_9_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2019.107049"},{"key":"e_1_2_9_5_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11047-020-09830-2"},{"key":"e_1_2_9_6_2","doi-asserted-by":"crossref","unstructured":"WangF. LinS. WuH. LiH. WangR. LuoX. andHeX. SPFusionNet: sketch segmentation using multi-modal data fusion 2019 IEEE International Conference on Multimedia and Expo (ICME) 2019 Shanghai China 1654\u20131659 https:\/\/doi.org\/10.1109\/ICME.2019.00285 2-s2.0-85070968895.","DOI":"10.1109\/ICME.2019.00285"},{"key":"e_1_2_9_7_2","doi-asserted-by":"crossref","unstructured":"ChenJ.andFangY. Deep cross-modality adaptation via semantics preserving adversarial learning for sketch-based 3d shape retrieval Proceedings of the European Conference on Computer Vision (ECCV) 2018 Munich Germany 605\u2013620.","DOI":"10.1007\/978-3-030-01261-8_37"},{"key":"e_1_2_9_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2019.12.117"},{"key":"e_1_2_9_9_2","doi-asserted-by":"publisher","DOI":"10.1117\/1.JEI.28.2.023037"},{"key":"e_1_2_9_10_2","doi-asserted-by":"crossref","unstructured":"WangL. QianC. WangJ. andFangY. Unsupervised learning of 3D model reconstruction from handdrawn sketches Proceedings of the 26th ACM international conference on Multimedia 2018 Seoul Republic of Korea 1820\u20131828 https:\/\/doi.org\/10.1145\/3240508.3240699 2-s2.0-85058219421.","DOI":"10.1145\/3240508.3240699"},{"key":"e_1_2_9_11_2","doi-asserted-by":"crossref","unstructured":"LunZ. GadelhaM. KalogerakisE. MajiS. andWangR. 3D shape reconstruction from sketches via multi-view convolutional networks 2017 International Conference on 3D Vision (3DV) 2017 Qingdao China 67\u201377 https:\/\/doi.org\/10.1109\/3DV.2017.00018 2-s2.0-85048828257.","DOI":"10.1109\/3DV.2017.00018"},{"key":"e_1_2_9_12_2","doi-asserted-by":"publisher","DOI":"10.1145\/2487228.2487237"},{"key":"e_1_2_9_13_2","unstructured":"ResourceT. M. 2017 https:\/\/www.models-resource.com\/."},{"key":"e_1_2_9_14_2","unstructured":"ChangA. X. FunkhouserT. GuibasL. HanrahanP. HuangQ. LiZ. SavareseS. SavvaM. SongS. andSuH. ShapeNet: an information-rich 3D model repository 2015 https:\/\/arxiv.org\/abs\/1512.03012."},{"key":"e_1_2_9_15_2","doi-asserted-by":"crossref","unstructured":"TatarchenkoM. DosovitskiyA. andBroxT. Multi-view 3D models from single images with a convolutional network 9911 Computer Vision \u2013 ECCV 2016: 14th European Conference 2016 Amsterdam The Netherlands 322\u2013337 https:\/\/doi.org\/10.1007\/978-3-319-46478-7_20 2-s2.0-84990053692.","DOI":"10.1007\/978-3-319-46478-7_20"},{"key":"e_1_2_9_16_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"e_1_2_9_17_2","doi-asserted-by":"crossref","unstructured":"ChoyC. B. XuD. GwakJ. ChenK. andSavareseS. 3d-r2n2: a unified approach for single and multi-view 3d object reconstruction 9912 Computer Vision \u2013 ECCV 2016: 14th European Conference 2016 Amsterdam The Netherlands 628\u2013644 https:\/\/doi.org\/10.1007\/978-3-319-46484-8_38 2-s2.0-84990029971.","DOI":"10.1007\/978-3-319-46484-8_38"},{"key":"e_1_2_9_18_2","doi-asserted-by":"publisher","DOI":"10.1145\/2661229.2661280"},{"key":"e_1_2_9_19_2","doi-asserted-by":"publisher","DOI":"10.1155\/2021\/6655125"},{"key":"e_1_2_9_20_2","article-title":"A computational model of emotion based on audio-visual stimuli understanding and personalized regulation with concurrency","volume":"17","author":"Jiang D.","year":"2021","journal-title":"Concurrency and Computation: Practice and Experience"},{"key":"e_1_2_9_21_2","doi-asserted-by":"publisher","DOI":"10.1109\/JAS.2020.1003387"},{"key":"e_1_2_9_22_2","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2021.3051251"},{"key":"e_1_2_9_23_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2872420"},{"key":"e_1_2_9_24_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2970250"},{"key":"e_1_2_9_25_2","doi-asserted-by":"publisher","DOI":"10.3390\/electronics9091474"},{"key":"e_1_2_9_26_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.11.026"},{"key":"e_1_2_9_27_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3019354"}],"container-title":["Wireless Communications and Mobile Computing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/wcmc\/2021\/5577530.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/wcmc\/2021\/5577530.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1155\/2021\/5577530","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,7]],"date-time":"2024-08-07T11:11:32Z","timestamp":1723029092000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1155\/2021\/5577530"}},"subtitle":[],"editor":[{"given":"Amr","family":"Tolba","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2021,1]]},"references-count":27,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,1]]}},"alternative-id":["10.1155\/2021\/5577530"],"URL":"https:\/\/doi.org\/10.1155\/2021\/5577530","archive":["Portico"],"relation":{},"ISSN":["1530-8669","1530-8677"],"issn-type":[{"type":"print","value":"1530-8669"},{"type":"electronic","value":"1530-8677"}],"subject":[],"published":{"date-parts":[[2021,1]]},"assertion":[{"value":"2021-01-08","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2021-03-26","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2021-04-27","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"5577530"}}