{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T15:54:50Z","timestamp":1790610890682,"version":"4.1.0"},"reference-count":47,"publisher":"Springer Science and Business Media LLC","issue":"7-8","license":[{"start":{"date-parts":[[2019,3,29]],"date-time":"2019-03-29T00:00:00Z","timestamp":1553817600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"name":"Elite Scholar Program of Tianjin University","award":["2019XRX-0035"],"award-info":[{"award-number":["2019XRX-0035"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61772359"],"award-info":[{"award-number":["61772359"]}],"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":["61872267"],"award-info":[{"award-number":["61872267"]}],"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":["61572356"],"award-info":[{"award-number":["61572356"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Tianjin New Generation Articial Intelligence Major Program","award":["18ZXZNGX00150"],"award-info":[{"award-number":["18ZXZNGX00150"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2020,2]]},"DOI":"10.1007\/s11042-019-7521-8","type":"journal-article","created":{"date-parts":[[2019,3,29]],"date-time":"2019-03-29T15:02:18Z","timestamp":1553871738000},"page":"4699-4711","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["3D model retrieval based on multi-view attentional convolutional neural network"],"prefix":"10.1007","volume":"79","author":[{"given":"An-An","family":"Liu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"He-Yu","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Meng-Jie","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei-Zhi","family":"Nie","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2019,3,29]]},"reference":[{"key":"7521_CR1","unstructured":"Bahdanau D, Cho K, Bengio Y (2014) Neural machine translation by jointly learning to align and translate. arXiv: 1409.0473"},{"key":"7521_CR2","doi-asserted-by":"crossref","unstructured":"Bai S, Bai X, Zhou Z, Zhang Z, Latecki LJ (2016) GIFT: a real-time and scalable 3d shape search engine. In: CVPR 2016, Las vegas, NV, USA, June 27-30, 2016, pp 5023\u20135032","DOI":"10.1109\/CVPR.2016.543"},{"issue":"4","key":"7521_CR3","doi-asserted-by":"publisher","first-page":"499","DOI":"10.1016\/j.autcon.2007.09.001","volume":"17","author":"F Bosche","year":"2008","unstructured":"Bosche F, Haas CT (2008) Automated retrieval of 3d cad model objects in construction range images. Autom Constr 17(4):499\u2013512","journal-title":"Autom Constr"},{"key":"7521_CR4","unstructured":"Cheng Z, Chang X, Zhu L, Catherine Kanjirathinkal R, Kankanhalli MS (2018) MMALFM: explainable recommendation by leveraging reviews and images. arXiv: 1811.05318"},{"key":"7521_CR5","doi-asserted-by":"crossref","unstructured":"Dalal N, Triggs B (2005) Histograms of oriented gradients for human detection. In: CVPR 2005, 20-26 June 2005, San Diego, CA, USA, pp 886\u2013893","DOI":"10.1109\/CVPR.2005.177"},{"issue":"9","key":"7521_CR6","doi-asserted-by":"publisher","first-page":"4290","DOI":"10.1109\/TIP.2012.2199502","volume":"21","author":"Y Gao","year":"2012","unstructured":"Gao Y, Wang M, Tao D, Ji R, Dai Q (2012) 3-d object retrieval and recognition with hypergraph analysis. IEEE Trans Image Processing 21(9):4290\u20134303","journal-title":"IEEE Trans Image Processing"},{"issue":"3","key":"7521_CR7","first-page":"35:1","volume":"8","author":"Y Gao","year":"2017","unstructured":"Gao Y, Zhang H, Zhao X, Yan S (2017) Event classification in microblogs via social tracking. ACM TIST 8(3):35:1\u201335:14","journal-title":"ACM TIST"},{"issue":"10","key":"7521_CR8","doi-asserted-by":"publisher","first-page":"2115","DOI":"10.1109\/TMM.2016.2581483","volume":"18","author":"Y Gao","year":"2016","unstructured":"Gao Y, Zhen Y, Li H, Chua T (2016) Filtering of brand-related microblogs using social-smooth multiview embedding. IEEE Trans Multimedia 18(10):2115\u20132126","journal-title":"IEEE Trans Multimedia"},{"key":"7521_CR9","doi-asserted-by":"crossref","unstructured":"Garcia-Garcia A, Gomez-Donoso F, Rodr\u00edguez JG, Orts-Escolano S, Cazorla M, L\u00f3pez JA (2016) Pointnet: a 3d convolutional neural network for real-time object class recognition. In: IJCNN 2016, Vancouver, BC, Canada, July 24\u201329, 2016, pp 1578\u20131584","DOI":"10.1109\/IJCNN.2016.7727386"},{"issue":"2","key":"7521_CR10","doi-asserted-by":"publisher","first-page":"362","DOI":"10.1109\/TITB.2005.863875","volume":"10","author":"G Gu\u00e9tat","year":"2006","unstructured":"Gu\u00e9tat G, Maitre M, Joly L, Lai SL, Lee T, Shinagawa Y (2006) Automatic 3-d grayscale volume matching and shape analysis. IEEE Trans Inf Technol Biomed 10(2):362","journal-title":"IEEE Trans Inf Technol Biomed"},{"key":"7521_CR11","doi-asserted-by":"crossref","unstructured":"Hilaga M, Shinagawa Y, Komura T, Kunii TL (2001) Topology matching for fully automatic similarity estimation of 3d shapes. In: SIGGRAPH 2001, Los Angeles, California, USA, August 12\u201317, 2001, pp 203\u2013212","DOI":"10.1145\/383259.383282"},{"key":"7521_CR12","unstructured":"Ip CY, Lapadat D, Sieger L, Regli WC (2002) Using shape distributions to compare solid models. In: Seventh ACM symposium on solid modeling and applications, max-planck-institut f\u00fcr informatik, saarbr\u00fccken, Germany, June 17\u201321, 2002, pp 273\u2013280"},{"key":"7521_CR13","doi-asserted-by":"crossref","unstructured":"Johns E, Leutenegger S, Davison AJ (2016) Pairwise decomposition of image sequences for active multi-view recognition. In: CVPR 2016, Las Vegas, NV, USA, June 27\u201330, 2016, pp 3813\u20133822","DOI":"10.1109\/CVPR.2016.414"},{"key":"7521_CR14","unstructured":"Kanezaki A (2016) Rotationnet: learning object classification using unsupervised viewpoint estimation. arXiv: 1603.06208"},{"issue":"1\u20132","key":"7521_CR15","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1016\/S0923-5965(00)00019-9","volume":"16","author":"W Kim","year":"2000","unstructured":"Kim W, Kim Y (2000) A region-based shape descriptor using zernike moments. Sig Proc Image Comm 16(1\u20132):95\u2013102","journal-title":"Sig Proc Image Comm"},{"issue":"6","key":"7521_CR16","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1145\/3065386","volume":"60","author":"A Krizhevsky","year":"2017","unstructured":"Krizhevsky A, Sutskever I, Hinton GE (2017) Imagenet classification with deep convolutional neural networks. Commun ACM 60(6):84\u201390","journal-title":"Commun ACM"},{"key":"7521_CR17","unstructured":"Little JJ (1985) Determining object attitude from extended gaussian images. In: Proceedings of the 9th international joint conference on artificial intelligence. Los Angeles, CA, USA, August 1985, pp 960\u2013963"},{"issue":"5","key":"7521_CR18","doi-asserted-by":"publisher","first-page":"2103","DOI":"10.1109\/TIP.2016.2540802","volume":"25","author":"A Liu","year":"2016","unstructured":"Liu A, Nie W, Gao Y, Su Y (2016) Multi-modal clique-graph matching for view-based 3d model retrieval. IEEE Trans Image Process 25(5):2103\u20132116","journal-title":"IEEE Trans Image Process"},{"issue":"3","key":"7521_CR19","doi-asserted-by":"crossref","first-page":"916","DOI":"10.1109\/TCYB.2017.2664503","volume":"48","author":"A Liu","year":"2018","unstructured":"Liu A, Nie W, Gao Y, Su Y (2018) View-based 3-d model retrieval: a benchmark. IEEE Trans Cybernetics 48(3):916\u2013928","journal-title":"IEEE Trans Cybernetics"},{"issue":"2","key":"7521_CR20","doi-asserted-by":"publisher","first-page":"853","DOI":"10.1109\/TIP.2018.2872879","volume":"28","author":"A Liu","year":"2019","unstructured":"Liu A, Xu N, Nie W, Su Y, Zhang Y (2019) Multi-domain and multi-task learning for human action recognition. IEEE Trans Image Process 28(2):853\u2013867","journal-title":"IEEE Trans Image Process"},{"key":"7521_CR21","doi-asserted-by":"crossref","unstructured":"Liu S, Giles CL, Ororbia A (2018) Learning a hierarchical latent-variable model of 3d shapes. In: 3DV pp 542\u2013551","DOI":"10.1109\/3DV.2018.00068"},{"key":"7521_CR22","doi-asserted-by":"publisher","first-page":"502","DOI":"10.1016\/j.jvcir.2017.01.010","volume":"48","author":"W Liu","year":"2017","unstructured":"Liu W, Gao Y, Ma H, Yu S, Nie J (2017) Online multi-objective optimization for live video forwarding across video data centers. J Vis Commun Image Represent 48:502\u2013513","journal-title":"J Vis Commun Image Represent"},{"issue":"3\u20134","key":"7521_CR23","doi-asserted-by":"publisher","first-page":"457","DOI":"10.1007\/s12021-018-9362-4","volume":"16","author":"W Liu","year":"2018","unstructured":"Liu W, Zhang C, Ma H, Li S (2018) Learning efficient spatial-temporal gait features with deep learning for human identification. Neuroinformatics 16(3\u20134):457\u2013471","journal-title":"Neuroinformatics"},{"issue":"3","key":"7521_CR24","doi-asserted-by":"publisher","first-page":"645","DOI":"10.1109\/TMM.2017.2751966","volume":"20","author":"X Liu","year":"2018","unstructured":"Liu X, Liu W, Mei T, Ma H (2018) PROVID: progressive and multimodal vehicle reidentification for large-scale urban surveillance. IEEE Trans Multimedia 20 (3):645\u2013658","journal-title":"IEEE Trans Multimedia"},{"issue":"1","key":"7521_CR25","doi-asserted-by":"publisher","first-page":"76","DOI":"10.1109\/MMUL.2017.265091429","volume":"25","author":"H Ma","year":"2018","unstructured":"Ma H, Liu W (2018) A progressive search paradigm for the internet of things. IEEE MultiMedia 25(1):76\u201386","journal-title":"IEEE MultiMedia"},{"issue":"2-3","key":"7521_CR26","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1007\/s11263-009-0280-7","volume":"89","author":"A Makadia","year":"2010","unstructured":"Makadia A, Daniilidis K (2010) Spherical correlation of visual representations for 3d model retrieval. Int J Comput Vis 89(2-3):193\u2013210","journal-title":"Int J Comput Vis"},{"key":"7521_CR27","doi-asserted-by":"crossref","unstructured":"Maturana D, Scherer S (2015) Voxnet: a 3d convolutional neural network for real-time object recognition. In: IROS 2015, Hamburg, Germany, September 28 - October 2, 2015, pp 922\u2013928","DOI":"10.1109\/IROS.2015.7353481"},{"issue":"13","key":"7521_CR28","doi-asserted-by":"publisher","first-page":"3812","DOI":"10.1093\/nar\/gkg509","volume":"31","author":"PC Ng","year":"2003","unstructured":"Ng PC, Henikoff S (2003) SIFT: predicting amino acid changes that affect protein function. Nucleic Acids Res 31(13):3812\u20133814","journal-title":"Nucleic Acids Res"},{"issue":"6","key":"7521_CR29","doi-asserted-by":"publisher","first-page":"311","DOI":"10.1145\/360825.360839","volume":"18","author":"BT Phong","year":"1975","unstructured":"Phong BT (1975) Illumination for computer generated pictures. Commun ACM 18(6):311\u2013317","journal-title":"Commun ACM"},{"key":"7521_CR30","unstructured":"Qi CR, Yi L, Su H, Guibas LJ (2017) Pointnet++: deep hierarchical feature learning on point sets in a metric space. In: NIPS 2017, 4-9 December 2017, Long Beach, CA, USA, pp 5105\u20135114"},{"key":"7521_CR31","unstructured":"Ren M, Niu L, Fang Y (2017) 3d-a-nets: 3d deep dense descriptor for volumetric shapes with adversarial networks. arXiv: 1711.10108"},{"key":"7521_CR32","unstructured":"Sfikas K, Theoharis T, Pratikakis I (2017) Exploiting the PANORAMA representation for convolutional neural network classification and retrieval. In: Eurographics workshop on 3d object retrieval, 3DOR 2017, Lyon, France, April 23-24, 2017"},{"issue":"12","key":"7521_CR33","doi-asserted-by":"publisher","first-page":"2339","DOI":"10.1109\/LSP.2015.2480802","volume":"22","author":"B Shi","year":"2015","unstructured":"Shi B, Bai S, Zhou Z, Bai X (2015) Deeppano: deep panoramic representation for 3-d shape recognition. IEEE Signal Process Lett 22(12):2339\u20132343","journal-title":"IEEE Signal Process Lett"},{"issue":"4","key":"7521_CR34","doi-asserted-by":"publisher","first-page":"261","DOI":"10.1007\/s00138-007-0097-8","volume":"19","author":"K Siddiqi","year":"2008","unstructured":"Siddiqi K, Zhang J, Macrini D, Shokoufandeh A, Bouix S, Dickinson SJ (2008) Retrieving articulated 3-d models using medial surfaces. Mach Vis Appl 19(4):261\u2013275","journal-title":"Mach Vis Appl"},{"key":"7521_CR35","doi-asserted-by":"crossref","unstructured":"Su H, Maji S, Kalogerakis E, Learned-Miller EG (2015) Multi-view convolutional neural networks for 3d shape recognition. In: ICCV 2015, Santiago, Chile, December 7\u201313, 2015, pp 945\u2013953","DOI":"10.1109\/ICCV.2015.114"},{"issue":"9","key":"7521_CR36","doi-asserted-by":"publisher","first-page":"1591","DOI":"10.1109\/TMM.2015.2457676","volume":"17","author":"H Tabia","year":"2015","unstructured":"Tabia H, Laga H (2015) Covariance-based descriptors for efficient 3d shape matching, retrieval, and classification. IEEE Trans Multimedia 17(9):1591\u20131603","journal-title":"IEEE Trans Multimedia"},{"issue":"1","key":"7521_CR37","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1142\/S021946780300097X","volume":"3","author":"JWH Tangelder","year":"2003","unstructured":"Tangelder JWH, Veltkamp RC (2003) Polyhedral model retrieval using weighted point sets. Int J Image Graphics 3(1):209","journal-title":"Int J Image Graphics"},{"key":"7521_CR38","doi-asserted-by":"publisher","first-page":"620","DOI":"10.1016\/j.neucom.2014.03.091","volume":"151","author":"X Wang","year":"2015","unstructured":"Wang X, Nie W (2015) 3d model retrieval with weighted locality-constrained group sparse coding. Neurocomputing 151:620\u2013625","journal-title":"Neurocomputing"},{"issue":"5","key":"7521_CR39","doi-asserted-by":"publisher","first-page":"1026","DOI":"10.1109\/TMM.2007.898915","volume":"9","author":"HS Wong","year":"2007","unstructured":"Wong HS, Ma B, Yu Z, Yeung PF, Ip HHS (2007) 3-d head model retrieval using a single face view query. IEEE Trans on Multimedia 9(5):1026\u20131036","journal-title":"IEEE Trans on Multimedia"},{"key":"7521_CR40","unstructured":"Wu J, Zhang C, Xue T, Freeman B, Tenenbaum J (2016) Learning a probabilistic latent space of object shapes via 3d generative-adversarial modeling. In: NIPS 2016, December 5\u201310, 2016, Barcelona, Spain, pp 82\u201390"},{"key":"7521_CR41","unstructured":"Wu Z, Song S, Khosla A, Yu F, Zhang L, Tang X, Xiao J (2015) 3d shapenets: a deep representation for volumetric shapes. In: CVPR 2015, Boston, MA, USA, June 7-12, 2015, pp 1912\u20131920"},{"issue":"7","key":"7521_CR42","doi-asserted-by":"publisher","first-page":"1335","DOI":"10.1109\/TPAMI.2016.2596722","volume":"39","author":"J Xie","year":"2017","unstructured":"Xie J, Dai G, Zhu F, Wong EK, Fang Y (2017) Deepshape: deep-learned shape descriptor for 3d shape retrieval. IEEE Trans Pattern Anal Mach Intell 39(7):1335\u20131345","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"7521_CR43","doi-asserted-by":"crossref","unstructured":"Xie J, Zheng Z, Gao R, Wang W, Zhu S, Wu YN (2018) Learning descriptor networks for 3d shape synthesis and analysis. arXiv: 1804.00586","DOI":"10.1109\/CVPR.2018.00900"},{"key":"7521_CR44","doi-asserted-by":"crossref","unstructured":"Zanuttigh P, Minto L (2017) Deep learning for 3d shape classification from multiple depth maps. In: ICIP 2017, Beijing, China, September 17\u201320, 2017, pp 3615\u20133619","DOI":"10.1109\/ICIP.2017.8296956"},{"key":"7521_CR45","unstructured":"Zaremba W, Sutskever I, Vinyals O (2014) Recurrent neural network regularization. arXiv: 1409.2329"},{"key":"7521_CR46","doi-asserted-by":"publisher","first-page":"533","DOI":"10.1016\/j.neucom.2014.03.092","volume":"151","author":"S Zhao","year":"2015","unstructured":"Zhao S, Chen L, Yao H, Zhang Y, Sun X (2015) Strategy for dynamic 3d depth data matching towards robust action retrieval. Neurocomputing 151:533\u2013543","journal-title":"Neurocomputing"},{"issue":"99","key":"7521_CR47","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TNNLS.2017.2705115","volume":"PP","author":"X Zhao","year":"2017","unstructured":"Zhao X, Wang N, Zhang Y, Du S, Gao Y, Sun J (2017) Beyond pairwise matching: person reidentification via high-order relevance learning. IEEE Trans Neural Netw Learn Syst PP(99):1\u201314","journal-title":"IEEE Trans Neural Netw Learn Syst"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-019-7521-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11042-019-7521-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-019-7521-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,14]],"date-time":"2022-09-14T20:59:52Z","timestamp":1663189192000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11042-019-7521-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,3,29]]},"references-count":47,"journal-issue":{"issue":"7-8","published-print":{"date-parts":[[2020,2]]}},"alternative-id":["7521"],"URL":"https:\/\/doi.org\/10.1007\/s11042-019-7521-8","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,3,29]]},"assertion":[{"value":"17 September 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 March 2019","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 March 2019","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 March 2019","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}