{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T04:08:06Z","timestamp":1777522086531,"version":"3.51.4"},"reference-count":43,"publisher":"Institute of Electronics, Information and Communications Engineers (IEICE)","issue":"7","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEICE Trans. Inf. & Syst."],"published-print":{"date-parts":[[2021,7,1]]},"DOI":"10.1587\/transinf.2020edp7223","type":"journal-article","created":{"date-parts":[[2021,6,30]],"date-time":"2021-06-30T22:20:56Z","timestamp":1625091656000},"page":"1028-1038","source":"Crossref","is-referenced-by-count":2,"title":["Multi-View Texture Learning for Face Super-Resolution"],"prefix":"10.1587","volume":"E104.D","author":[{"given":"Yu","family":"WANG","sequence":"first","affiliation":[{"name":"Hubei Key Laboratory of Intelligent Robot, School of Computer Science and Engineering, Wuhan Institute of Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tao","family":"LU","sequence":"additional","affiliation":[{"name":"Hubei Key Laboratory of Intelligent Robot, School of Computer Science and Engineering, Wuhan Institute of Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Feng","family":"YAO","sequence":"additional","affiliation":[{"name":"Hubei Key Laboratory of Intelligent Robot, School of Computer Science and Engineering, Wuhan Institute of Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuntao","family":"WU","sequence":"additional","affiliation":[{"name":"Hubei Key Laboratory of Intelligent Robot, School of Computer Science and Engineering, Wuhan Institute of Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanduo","family":"ZHANG","sequence":"additional","affiliation":[{"name":"Hubei Key Laboratory of Intelligent Robot, School of Computer Science and Engineering, Wuhan Institute of Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"532","reference":[{"key":"1","doi-asserted-by":"crossref","unstructured":"[1] J. Deng, J. Guo, N. Xue, and S. Zafeiriou, \u201cArcface: Additive angular margin loss for deep face recognition,\u201d Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp.4690-4699, 2019. 10.1109\/cvpr.2019.00482","DOI":"10.1109\/CVPR.2019.00482"},{"key":"2","doi-asserted-by":"crossref","unstructured":"[2] F. Schroff, D. Kalenichenko, and J. Philbin, \u201cFacenet: A unified embedding for face recognition and clustering,\u201d 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.815-823, 2015. 10.1109\/cvpr.2015.7298682","DOI":"10.1109\/CVPR.2015.7298682"},{"key":"3","doi-asserted-by":"publisher","unstructured":"[3] Z. Zhang, P. Luo, C.C. Loy, and X. Tang, \u201cLearning deep representation for face alignment with auxiliary attributes,\u201d IEEE Trans. Pattern Anal. Mach. Intell., vol.38, no.5, pp.918-930, 2016. 10.1109\/tpami.2015.2469286","DOI":"10.1109\/TPAMI.2015.2469286"},{"key":"4","doi-asserted-by":"publisher","unstructured":"[4] K. Zhang, Z. Zhang, Z. Li, and Y. Qiao, \u201cJoint face detection and alignment using multitask cascaded convolutional networks,\u201d IEEE Signal Process. Lett., vol.23, no.10, pp.1499-1503, 2016. 10.1109\/lsp.2016.2603342","DOI":"10.1109\/LSP.2016.2603342"},{"key":"5","doi-asserted-by":"publisher","unstructured":"[5] J. Deng, G. Trigeorgis, Y. Zhou, and S. Zafeiriou, \u201cJoint multi-view face alignment in the wild,\u201d IEEE Transactions on Image Processing, vol.28, no.7, pp.3636-3648, 2019. 10.1109\/tip.2019.2899267","DOI":"10.1109\/TIP.2019.2899267"},{"key":"6","doi-asserted-by":"crossref","unstructured":"[6] Y. Li, S. Liu, J. Yang, and M.-H. Yang, \u201cGenerative face completion,\u201d 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.5892-5900, 2017. 10.1109\/cvpr.2017.624","DOI":"10.1109\/CVPR.2017.624"},{"key":"7","unstructured":"[7] P. Luo, X. Wang, and X. Tang, \u201cHierarchical face parsing via deep learning,\u201d 2012 IEEE Conference on Computer Vision and Pattern Recognition, pp.2480-2487, 2012. 10.1109\/cvpr.2012.6247963"},{"key":"8","doi-asserted-by":"publisher","unstructured":"[8] K. Nasrollahi and T.B. Moeslund, \u201cSuper-resolution: a comprehensive survey,\u201d Mach. Vision. Appl., vol.25, no.6, pp.1423-1468, 2014. 10.1007\/s00138-014-0623-4","DOI":"10.1007\/s00138-014-0623-4"},{"key":"9","doi-asserted-by":"publisher","unstructured":"[9] L. Zhang and X. Wu, \u201cAn edge-guided image interpolation algorithm via directional filtering and data fusion,\u201d IEEE Trans. Image Process., vol.15, no.8, pp.2226-2238, 2006. 10.1109\/tip.2006.877407","DOI":"10.1109\/TIP.2006.877407"},{"key":"10","unstructured":"[10] T.R. Y, \u201cMultiple frame image restoration and registration,\u201d Computer Vision and Image Processing, 1984."},{"key":"11","doi-asserted-by":"publisher","unstructured":"[11] K. Zeng, T. Lu, X. Liang, K. Liu, H. Chen, and Y. Zhang, \u201cFace super-resolution via bilayer contextual representation,\u201d Signal Processing-image Communication, vol.75, pp.147-157, 2019. 10.1016\/j.image.2019.03.019","DOI":"10.1016\/j.image.2019.03.019"},{"key":"12","unstructured":"[12] S. Baker and T. Kanade, \u201cHallucinating faces,\u201d Proc. 4th IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580), pp.83-88, 2000. 10.1109\/afgr.2000.840616"},{"key":"13","doi-asserted-by":"publisher","unstructured":"[13] J. Yang, J. Wright, T.S. Huang, and Y. Ma, \u201cImage super-resolution via sparse representation,\u201d IEEE Trans. Image Process., vol.19, no.11, pp.2861-2873, Nov. 2010. 10.1109\/tip.2010.2050625","DOI":"10.1109\/TIP.2010.2050625"},{"key":"14","doi-asserted-by":"publisher","unstructured":"[14] X. Ma, H. Huang, S. Wang, and C. Qi, \u201cA simple approach to multiview face hallucination,\u201d IEEE Signal Process. Lett., vol.17, no.6, pp.579-582, June 2010. 10.1109\/lsp.2010.2047317","DOI":"10.1109\/LSP.2010.2047317"},{"key":"15","doi-asserted-by":"crossref","unstructured":"[15] J. Jiang, R. Hu, Z. Han, Z. Wang, T. Lu, and J. Chen, \u201cLocality-constraint iterative neighbor embedding for face hallucination,\u201d 2013 IEEE International Conference on Multimedia and Expo (ICME), pp.1-6, July 2013. 10.1109\/icme.2013.6607455","DOI":"10.1109\/ICME.2013.6607455"},{"key":"16","doi-asserted-by":"publisher","unstructured":"[16] J. Jiang, R. Hu, Z. Wang, Z. Han, and J. Ma, \u201cFacial image hallucination through coupled-layer neighbor embedding,\u201d IEEE Trans. Circuits Syst. Video Technol., vol.26, no.9, pp.1674-1684, Sept. 2016. 10.1109\/tcsvt.2015.2433538","DOI":"10.1109\/TCSVT.2015.2433538"},{"key":"17","doi-asserted-by":"publisher","unstructured":"[17] J.-J. Huang and W.-C. Siu, \u201cLearning hierarchical decision trees for single-image super-resolution,\u201d IEEE Trans. Circuits Syst. Video Technol., vol.27, no.5, pp.937-950, May 2017. 10.1109\/tcsvt.2015.2513661","DOI":"10.1109\/TCSVT.2015.2513661"},{"key":"18","doi-asserted-by":"crossref","unstructured":"[18] Z.-S. Liu, W.-C. Siu, and J.-J. Huang, \u201cImage super-resolution via weighted random forest,\u201d 2017 IEEE International Conference on Industrial Technology (ICIT), pp.1019-1023, March 2017. 10.1109\/icit.2017.7915501","DOI":"10.1109\/ICIT.2017.7915501"},{"key":"19","doi-asserted-by":"crossref","unstructured":"[19] Z.-S. Liu, W.-C. Siu, and Y.-L. Chan, \u201cFast image super-resolution via randomized multi-split forests,\u201d 2017 IEEE International Symposium on Circuits and Systems (ISCAS), pp.1-4, May 2017. 10.1109\/iscas.2017.8050991","DOI":"10.1109\/ISCAS.2017.8050991"},{"key":"20","doi-asserted-by":"crossref","unstructured":"[20] C. Dong, C.C. Loy, K. He, and X. Tang, \u201cLearning a deep convolutional network for image super-resolution,\u201d Computer Vision-ECCV 2014, Lecture Notes in Computer Science, vol.8692, pp.184-199, Springer International Publishing, Cham, 2014. 10.1007\/978-3-319-10593-2_13","DOI":"10.1007\/978-3-319-10593-2_13"},{"key":"21","doi-asserted-by":"crossref","unstructured":"[21] X. Yu and F. Porikli, \u201cHallucinating very low-resolution unaligned and noisy face images by transformative discriminative autoencoders,\u201d 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.5367-5375, July 2017. 10.1109\/cvpr.2017.570","DOI":"10.1109\/CVPR.2017.570"},{"key":"22","doi-asserted-by":"crossref","unstructured":"[22] X. Yang, T. Lu, J. Wang, Y. Zhang, Y. Wu, Z. Wang, and Z. Xiong, \u201cEnhanced discriminative generative adversarial network for face super-resolution,\u201d Pacific Rim Conference on Multimedia, vol.11165, pp.441-452, Springer, 2018. 10.1007\/978-3-030-00767-6_41","DOI":"10.1007\/978-3-030-00767-6_41"},{"key":"23","doi-asserted-by":"publisher","unstructured":"[23] T. Lu, X. Hao, Y. Zhang, K. Liu, and Z. Xiong, \u201cParallel region-based deep residual networks for face hallucination,\u201d IEEE Access, vol.7, pp.81266-81278, 2019. 10.1109\/access.2019.2923023","DOI":"10.1109\/ACCESS.2019.2923023"},{"key":"24","doi-asserted-by":"publisher","unstructured":"[24] K. Jia and S. Gong, \u201cGeneralized face super-resolution,\u201d IEEE Trans. Image Process., vol.17, no.6, pp.873-886, June 2008. 10.1109\/tip.2008.922421","DOI":"10.1109\/TIP.2008.922421"},{"key":"25","unstructured":"[25] E. Ustinova and V.S. Lempitsky, \u201cDeep multi-frame face hallucination for face identification,\u201d CoRR, vol.abs\/1709.03196, 2017."},{"key":"26","doi-asserted-by":"crossref","unstructured":"[26] L. Wang, Y. Wang, Z. Liang, Z. Lin, J. Yang, W. An, and Y. Guo, \u201cLearning parallax attention for stereo image super-resolution,\u201d CoRR, vol.abs\/1903.05784, 2019. 10.1109\/cvpr.2019.01253","DOI":"10.1109\/CVPR.2019.01253"},{"key":"27","doi-asserted-by":"crossref","unstructured":"[27] J. Kim, J.K. Lee, and K.M. Lee, \u201cAccurate image super-resolution using very deep convolutional networks,\u201d CoRR, vol. abs\/ 1511. 04587, 2015. 10.1109\/cvpr.2016.182","DOI":"10.1109\/CVPR.2016.182"},{"key":"28","doi-asserted-by":"crossref","unstructured":"[28] C. Ledig, L. Theis, F. Huszar, J. Caballero, A.P. Aitken, A. Tejani, J. Totz, Z. Wang, and W. Shi, \u201cPhoto-realistic single image super-resolution using a generative adversarial network,\u201d CoRR, vol.abs\/1609.04802, 2016. 10.1109\/cvpr.2017.19","DOI":"10.1109\/CVPR.2017.19"},{"key":"29","doi-asserted-by":"crossref","unstructured":"[29] Y. Liu, Y. Wang, N. Li, X. Cheng, Y. Zhang, Y. Huang, and G. Lu, \u201cAn attention-based approach for single image super resolution,\u201d CoRR, vol.abs\/1807.06779, 2018. 10.1109\/icpr.2018.8545760","DOI":"10.1109\/ICPR.2018.8545760"},{"key":"30","doi-asserted-by":"crossref","unstructured":"[30] X. Wang, R.B. Girshick, A. Gupta, and K. He, \u201cNon-local neural networks,\u201d CoRR, vol.abs\/1711.07971, 2017. 10.1109\/cvpr.2018.00813","DOI":"10.1109\/CVPR.2018.00813"},{"key":"31","unstructured":"[31] H. Zhang, I. Goodfellow, D. Metaxas, and A. Odena, \u201cSelf-attention generative adversarial networks,\u201d arXiv preprint arXiv:1805.08318, 2018."},{"key":"32","doi-asserted-by":"crossref","unstructured":"[32] J. Fu, J. Liu, H. Tian, Y. Li, Y. Bao, Z. Fang, and H. Lu, \u201cDual attention network for scene segmentation,\u201d Proc. IEEE Conference on Computer Vision and Pattern Recognition, pp.3146-3154, 2019. 10.1109\/cvpr.2019.00326","DOI":"10.1109\/CVPR.2019.00326"},{"key":"33","unstructured":"[33] A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A.N. Gomez, \u0141. Kaiser, and I. Polosukhin, \u201cAttention is all you need,\u201d Advances in neural information processing systems, pp.5998-6008, 2017."},{"key":"34","doi-asserted-by":"crossref","unstructured":"[34] Q. Zhang, Z. Cui, X. Niu, S. Geng, and Y. Qiao, \u201cImage segmentation with pyramid dilated convolution based on resnet and u-net,\u201d International Conference on Neural Information Processing, vol.10635, pp.364-372, Springer, 2017. 10.1007\/978-3-319-70096-0_38","DOI":"10.1007\/978-3-319-70096-0_38"},{"key":"35","doi-asserted-by":"crossref","unstructured":"[35] C. Godard, O.M. Aodha, and G.J. Brostow, \u201cUnsupervised monocular depth estimation with left-right consistency,\u201d Proc. IEEE Conference on Computer Vision and Pattern Recognition, pp.270-279, 2017. 10.1109\/cvpr.2017.699","DOI":"10.1109\/CVPR.2017.699"},{"key":"36","doi-asserted-by":"publisher","unstructured":"[36] C.E. Thomaz and G.A. Giraldi, \u201cA new ranking method for principal components analysis and its application to face image analysis,\u201d Image and Vision Computing, vol.28, no.6, pp.902-913, 2010. 10.1016\/j.imavis.2009.11.005","DOI":"10.1016\/j.imavis.2009.11.005"},{"key":"37","doi-asserted-by":"crossref","unstructured":"[37] L. Wolf, T. Hassner, and I. Maoz, \u201cFace recognition in unconstrained videos with matched background similarity,\u201d CVPR 2011, pp.529-534, 2011. 10.1109\/cvpr.2011.5995566","DOI":"10.1109\/CVPR.2011.5995566"},{"key":"38","doi-asserted-by":"crossref","unstructured":"[38] Y. Song, J. Zhang, S. He, L. Bao, and Q. Yang, \u201cLearning to hallucinate face images via component generation and enhancement,\u201d arXiv preprint arXiv:1708.00223, 2017. 10.24963\/ijcai.2017\/633","DOI":"10.24963\/ijcai.2017\/633"},{"key":"39","doi-asserted-by":"crossref","unstructured":"[39] Z. Zhang, Z. Wang, Z. Lin, and H. Qi, \u201cImage super-resolution by neural texture transfer,\u201d Proc. IEEE Conference on Computer Vision and Pattern Recognition, pp.7982-7991, 2019. 10.1109\/cvpr.2019.00817","DOI":"10.1109\/CVPR.2019.00817"},{"key":"40","doi-asserted-by":"publisher","unstructured":"[40] Z. Wang, A.C. Bovik, H.R. Sheikh, and E.P. Simoncelli, \u201cImage quality assessment: from error visibility to structural similarity,\u201d IEEE Trans. Image Process., vol.13, no.4, pp.600-612, 2004. 10.1109\/tip.2003.819861","DOI":"10.1109\/TIP.2003.819861"},{"key":"41","doi-asserted-by":"publisher","unstructured":"[41] H.R. Sheikh and A.C. Bovik, \u201cImage information and visual quality,\u201d IEEE Trans. Image Process., vol.15, no.2, pp.430-444, 2006. 10.1109\/tip.2005.859378","DOI":"10.1109\/TIP.2005.859378"},{"key":"42","doi-asserted-by":"publisher","unstructured":"[42] A. Mittal, R. Soundararajan, and A.C. Bovik, \u201cMaking a \u201ccompletely blind\u201d image quality analyzer,\u201d IEEE Signal Process. Lett., vol.20, no.3, pp.209-212, March 2013. 10.1109\/lsp.2012.2227726","DOI":"10.1109\/LSP.2012.2227726"},{"key":"43","unstructured":"[43] D.P. Kingma and J. Ba, \u201cAdam: A method for stochastic optimization,\u201d arXiv preprint arXiv:1412.6980, 2014."}],"container-title":["IEICE Transactions on Information and Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E104.D\/7\/E104.D_2020EDP7223\/_pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,7,3]],"date-time":"2021-07-03T06:43:16Z","timestamp":1625294596000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E104.D\/7\/E104.D_2020EDP7223\/_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,1]]},"references-count":43,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2021]]}},"URL":"https:\/\/doi.org\/10.1587\/transinf.2020edp7223","relation":{},"ISSN":["0916-8532","1745-1361"],"issn-type":[{"value":"0916-8532","type":"print"},{"value":"1745-1361","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,7,1]]},"article-number":"2020EDP7223"}}