{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T07:28:29Z","timestamp":1740122909847,"version":"3.37.3"},"reference-count":31,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2020,9,25]],"date-time":"2020-09-25T00:00:00Z","timestamp":1600992000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,9,25]],"date-time":"2020-09-25T00:00:00Z","timestamp":1600992000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100002701","name":"Ministry of Education","doi-asserted-by":"publisher","award":["2018R1D1A1A09082615"],"award-info":[{"award-number":["2018R1D1A1A09082615"]}],"id":[{"id":"10.13039\/501100002701","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2021,1]]},"DOI":"10.1007\/s11042-020-09495-0","type":"journal-article","created":{"date-parts":[[2020,9,25]],"date-time":"2020-09-25T21:02:44Z","timestamp":1601067764000},"page":"4023-4036","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["3D-2D deep convolutional neural network (DCNN) Cascade for robust video face identification"],"prefix":"10.1007","volume":"80","author":[{"given":"Kyeong Tae","family":"Kim","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bumshik","family":"Lee","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3438-8248","authenticated-orcid":false,"given":"Jae Young","family":"Choi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,9,25]]},"reference":[{"key":"9495_CR1","volume-title":"arXiv preprint arXiv:1801.07698","author":"J Deng","year":"2018","unstructured":"Deng J, et al (2018) Arcface: additive angular margin loss for deep face recognition. In: arXiv preprint arXiv:1801.07698"},{"issue":"4","key":"9495_CR2","doi-asserted-by":"publisher","first-page":"1002","DOI":"10.1109\/TPAMI.2017.2700390","volume":"40","author":"C Ding","year":"2018","unstructured":"Ding C, Tao D (2018) Trunk-branch ensemble convolutional neural networks for video-based face recognition. IEEE Trans Pattern Anal Mach Intell 40(4):1002\u20131014","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"9495_CR3","first-page":"249","volume-title":"Understanding the difficulty of training deep feedforward neural networks","author":"X Glorot","year":"2010","unstructured":"Glorot X, Bengio Y (2010) International conference on artificial intelligence and statistics. In: Understanding the difficulty of training deep feedforward neural networks, pp 249\u2013256"},{"key":"9495_CR4","doi-asserted-by":"crossref","unstructured":"Gong S, Yichun S, Jain AK (2019) Video face recognition: component-wise feature aggregation network (C-FAN). arXiv preprint arXiv:1902.07327","DOI":"10.1109\/ICB45273.2019.8987385"},{"key":"9495_CR5","unstructured":"Goyal P, et al (2017) Accurate, large minibatch SGD: training imagenet in 1 hour. arXiv:1706.02677"},{"key":"9495_CR6","doi-asserted-by":"publisher","first-page":"354","DOI":"10.1016\/j.patcog.2017.10.013","volume":"77","author":"J GU","year":"2018","unstructured":"GU J, et al (2018) Recent advances in convolutional neural networks. Pattern Recogn 77:354\u2013377","journal-title":"Pattern Recogn"},{"issue":"4","key":"9495_CR7","doi-asserted-by":"publisher","first-page":"713","DOI":"10.1109\/TPAMI.2014.2353635","volume":"37","author":"M Hayat","year":"2015","unstructured":"Hayat M, Bennamoun M, An S (2015) Deep reconstruction models for image set classification. IEEE Trans Pattern Anal Mach Intell 37(4):713\u2013727","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"9495_CR8","doi-asserted-by":"crossref","unstructured":"Hern\u00e1ndez-Dur\u00e1n M, Plasencia-Cala\u00f1a Y, M\u00e9ndez-V\u00e1zquez H (2018) Low-resolution face recognition with deep convolutional features in the dissimilarity space. International Workshop on Artificial Intelligence and Pattern Recognition, pp 95\u2013103","DOI":"10.1007\/978-3-030-01132-1_11"},{"key":"9495_CR9","doi-asserted-by":"crossref","unstructured":"Huang Z, Wang R, Shan S, Chen X (2014) Learning euclidean-to-riemannian metric for point-to-set classification. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition:1677\u20131684","DOI":"10.1109\/CVPR.2014.217"},{"issue":"12","key":"9495_CR10","doi-asserted-by":"publisher","first-page":"5967","DOI":"10.1109\/TIP.2015.2493448","volume":"24","author":"Z Huang","year":"2015","unstructured":"Huang Z, Shan S, Wang R, Zhang H, Lao S, Kuerban A, Chen X (2015) A benchmark and comparative study of video-based face recognition on cox face database. IEEE Trans Image Process 24(12):5967\u20135981","journal-title":"IEEE Trans Image Process"},{"key":"9495_CR11","doi-asserted-by":"crossref","unstructured":"Huang Z, Wang R, Shan S, Chen X (2015) Projection metric learning on Grassmann manifold with application to video based face recognition. Proc IEEE Conf Comput Vis Pattern Recognit:140\u2013149","DOI":"10.1109\/CVPR.2015.7298609"},{"key":"9495_CR12","unstructured":"Intra-Face (2013) http:\/\/humansensing.cs.cmu.edu\/intraface. Accessed June, 23, 2017"},{"key":"9495_CR13","volume-title":"arXiv:1807.11205","author":"X Jia","year":"2018","unstructured":"Jia X, et al (2018) Highly scalable deep learning training system with mixed-precision: training imagenet in four minutes. In: arXiv:1807.11205"},{"key":"9495_CR14","doi-asserted-by":"crossref","unstructured":"Karpathy A, et al (2014) Large-scale video classification with convolutional neural networks. Proc IEEE Conf Comput Vis Pattern Recognit:1725\u20131732","DOI":"10.1109\/CVPR.2014.223"},{"key":"9495_CR15","volume-title":"arXiv:1609.04836","author":"NS Keskar","year":"2017","unstructured":"Keskar NS, et al (2017) On large-batch training for deep learning: generalization gap and sharp minima. In: arXiv:1609.04836"},{"key":"9495_CR16","unstructured":"Kim M, Kumar S, Pavlovic V, Rowley H (2008) Face tracking and recognition with visual constraints in real-world videos. In IEEE Conf Computer Vision and Pattern Recognition:1\u20138"},{"key":"9495_CR17","doi-asserted-by":"crossref","unstructured":"Liao X, Li K, Zhu X, Liu KR (2020) Robust detection of image operator chain with two-stream convolutional neural network. IEEE Journal of Selected Topics in Signal Processing:1\u20131","DOI":"10.1109\/JSTSP.2020.3002391"},{"key":"9495_CR18","doi-asserted-by":"crossref","unstructured":"Lu J, Wang G, Deng W, Moulin P, Zhou J (2015) Multimanifold deep metric learning for image set classification. Proc IEEE Conf Comput Vis Pattern Recognit:1137\u20131145","DOI":"10.1109\/CVPR.2015.7298717"},{"issue":"3","key":"9495_CR19","doi-asserted-by":"publisher","first-page":"529","DOI":"10.1109\/TCSVT.2015.2412831","volume":"26","author":"J Lu","year":"2016","unstructured":"Lu J, Wang G, Moulin P (2016) Localized multifeature metric learning for image-set-based face recognition. IEEE Transactions on Circuits and Systems for Video Technology 26(3):529\u2013540","journal-title":"IEEE Transactions on Circuits and Systems for Video Technology"},{"key":"9495_CR20","unstructured":"Masters D, Luschi C (2018) Revisiting small batch training for deep neural networks. arXiv:1804.07612"},{"key":"9495_CR21","doi-asserted-by":"crossref","unstructured":"Parchami M, Bashbaghi S, Granger E (2017) Cnns with cross-correlation matching for face recognition in video surveillance using a single training sample per person. 2017 14th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), pp 1\u20136","DOI":"10.1109\/AVSS.2017.8078554"},{"key":"9495_CR22","doi-asserted-by":"crossref","unstructured":"Parchami M, Bashbaghi S, Granger E (2017) Video-based face recognition using ensemble of haar-like deep convolutional neural networks. IJCNN","DOI":"10.1109\/IJCNN.2017.7966443"},{"key":"9495_CR23","doi-asserted-by":"crossref","unstructured":"Parkhi OM, Vedaldi A, Zisserman A (2015) Deep face recognition. European Conference on Computer Vision, pp 1\u201312","DOI":"10.5244\/C.29.41"},{"key":"9495_CR24","doi-asserted-by":"crossref","unstructured":"Qi X, Liu C, Schuckers S (2018) Boosting face in video recognition via cnn based key frame extraction. 2018 International Conference on Biometrics (ICB), pp 132\u2013139","DOI":"10.1109\/ICB2018.2018.00030"},{"issue":"6\u20137","key":"9495_CR25","doi-asserted-by":"publisher","first-page":"701","DOI":"10.1007\/s11263-018-1135-x","volume":"127","author":"Y Rao","year":"2019","unstructured":"Rao Y, Lu J, Zhou J (2019) Learning discriminative aggregation network for video-based face recognition and person re-identification. Int J Comput Vis 127(6\u20137):701\u2013718","journal-title":"Int J Comput Vis"},{"key":"9495_CR26","doi-asserted-by":"crossref","unstructured":"Tran D, et al (2015) Learning spatiotemporal features with 3d convolutional networks. Proceedings of the IEEE International Conference on Computer Vision:4489\u20134497","DOI":"10.1109\/ICCV.2015.510"},{"key":"9495_CR27","doi-asserted-by":"crossref","unstructured":"Wang R, Chen X (2009) Manifold discriminant analysis. In CVPR, pp:429\u2013436","DOI":"10.1109\/CVPR.2009.5206850"},{"key":"9495_CR28","first-page":"293","volume":"60","author":"H Wang","year":"2009","unstructured":"Wang H, Wang Y, Cao Y (2009) Video-based face recognition: a survey. World Academy of Science, Eng Technol 60:293\u2013302","journal-title":"World Academy of Science, Eng Technol"},{"key":"9495_CR29","doi-asserted-by":"crossref","unstructured":"Wu Y, He K (2018) Group normalization. Proceedings of the European conference on computer vision (ECCV), pp 3\u201319","DOI":"10.1007\/978-3-030-01261-8_1"},{"key":"9495_CR30","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1016\/j.imavis.2016.07.008","volume":"58","author":"M Yang","year":"2016","unstructured":"Yang M, Wang X, Liu W, Shen L (2016) Joint regularized nearest points for image set based face recognition. Image Vis Comput 58:47\u201360","journal-title":"Image Vis Comput"},{"issue":"6","key":"9495_CR31","first-page":"7","volume":"4","author":"J Yang","year":"2017","unstructured":"Yang J, Ren P, Zhang D, Chen D, Wen F, Li H, Hua G (2017) Neural aggregation network for video face recognition. IEEE Conference on Computer Vision and Pattern Recognition 4(6):7","journal-title":"IEEE Conference on Computer Vision and Pattern Recognition"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-020-09495-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-020-09495-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-020-09495-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,20]],"date-time":"2022-11-20T14:37:30Z","timestamp":1668955050000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-020-09495-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,9,25]]},"references-count":31,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2021,1]]}},"alternative-id":["9495"],"URL":"https:\/\/doi.org\/10.1007\/s11042-020-09495-0","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"type":"print","value":"1380-7501"},{"type":"electronic","value":"1573-7721"}],"subject":[],"published":{"date-parts":[[2020,9,25]]},"assertion":[{"value":"16 February 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 July 2020","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 July 2020","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 September 2020","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}