{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,3]],"date-time":"2026-11-03T12:35:33Z","timestamp":1793709333712,"version":"4.6.1"},"publisher-location":"Cham","reference-count":48,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030208929","type":"print"},{"value":"9783030208936","type":"electronic"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-20893-6_38","type":"book-chapter","created":{"date-parts":[[2019,5,28]],"date-time":"2019-05-28T03:25:52Z","timestamp":1559013952000},"page":"605-621","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":86,"title":["Low-Resolution Face Recognition"],"prefix":"10.1007","author":[{"given":"Zhiyi","family":"Cheng","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiatian","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shaogang","family":"Gong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2019,5,29]]},"reference":[{"key":"38_CR1","doi-asserted-by":"crossref","unstructured":"Ahonen, T., Hadid, A., Pietikainen, M.: Face description with local binary patterns: application to face recognition. IEEE TPAMI (2006)","DOI":"10.1109\/TPAMI.2006.244"},{"key":"38_CR2","doi-asserted-by":"crossref","unstructured":"Ahonen, T., Rahtu, E., Ojansivu, V., Heikkila, J.: Recognition of blurred faces using local phase quantization. In: ICPR (2008)","DOI":"10.1109\/ICPR.2008.4761847"},{"key":"38_CR3","doi-asserted-by":"crossref","unstructured":"Bansal, A., Nanduri, A., Castillo, C., Ranjan, R., Chellappa, R.: UMDFaces: an annotated face dataset for training deep networks. arXiv (2016)","DOI":"10.1109\/BTAS.2017.8272731"},{"key":"38_CR4","doi-asserted-by":"crossref","unstructured":"Belhumeur, P.N., Hespanha, J.P., Kriegman, D.J.: Eigenfaces vs. Fisherfaces: recognition using class specific linear projection. IEEE TPAMI (1997)","DOI":"10.1007\/BFb0015522"},{"key":"38_CR5","doi-asserted-by":"publisher","first-page":"2144","DOI":"10.1109\/TIFS.2014.2359577","volume":"9","author":"L Best-Rowden","year":"2014","unstructured":"Best-Rowden, L., Han, H., Otto, C., Klare, B.F., Jain, A.K.: Unconstrained face recognition: identifying a person of interest from a media collection. IEEE Trans. Inf. Forensics Secur. 9, 2144\u20132157 (2014)","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"38_CR6","doi-asserted-by":"crossref","unstructured":"Biswas, S., Bowyer, K.W., Flynn, P.J.: Multidimensional scaling for matching low-resolution facial images. In: BTAS (2010)","DOI":"10.1109\/BTAS.2010.5634479"},{"key":"38_CR7","doi-asserted-by":"publisher","first-page":"2019","DOI":"10.1109\/TPAMI.2011.278","volume":"34","author":"S Biswas","year":"2012","unstructured":"Biswas, S., Bowyer, K.W., Flynn, P.J.: Multidimensional scaling for matching low-resolution face images. IEEE TPAMI 34, 2019\u20132030 (2012)","journal-title":"IEEE TPAMI"},{"key":"38_CR8","doi-asserted-by":"crossref","unstructured":"Chen, D., Cao, X., Wen, F., Sun, J.: Blessing of dimensionality: high-dimensional feature and its efficient compression for face verification. In: CVPR (2013)","DOI":"10.1109\/CVPR.2013.389"},{"key":"38_CR9","unstructured":"Cheng, Z., Zhu, X., Gong, S.: Surveillance face recognition challenge. arXiv preprint \n                      arXiv:1804.09691\n                      \n                     (2018)"},{"key":"38_CR10","first-page":"1217","volume":"39","author":"JY Choi","year":"2009","unstructured":"Choi, J.Y., Ro, Y.M., Plataniotis, K.N.: Color face recognition for degraded face images. IEEE TSMC (Part B) 39, 1217\u20131230 (2009)","journal-title":"IEEE TSMC (Part B)"},{"key":"38_CR11","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"184","DOI":"10.1007\/978-3-319-10593-2_13","volume-title":"Computer Vision \u2013 ECCV 2014","author":"C Dong","year":"2014","unstructured":"Dong, C., Loy, C.C., He, K., Tang, X.: Learning a deep convolutional network for image super-resolution. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8692, pp. 184\u2013199. Springer, Cham (2014). \n                      https:\/\/doi.org\/10.1007\/978-3-319-10593-2_13"},{"key":"38_CR12","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1016\/j.jvcir.2011.06.004","volume":"23","author":"C Fookes","year":"2012","unstructured":"Fookes, C., Lin, F., Chandran, V., Sridharan, S.: Evaluation of image resolution and super-resolution on face recognition performance. J. Vis. Commun. Image Represent. 23, 75\u201393 (2012)","journal-title":"J. Vis. Commun. Image Represent."},{"key":"38_CR13","doi-asserted-by":"crossref","unstructured":"Georghiades, A.S., Belhumeur, P.N., Kriegman, D.J.: From few to many: illumination cone models for face recognition under variable lighting and pose. IEEE TPAMI (2001)","DOI":"10.1109\/34.927464"},{"key":"38_CR14","doi-asserted-by":"publisher","first-page":"807","DOI":"10.1016\/j.imavis.2009.08.002","volume":"28","author":"R Gross","year":"2010","unstructured":"Gross, R., Matthews, I., Cohn, J., Kanade, T., Baker, S.: Multi-pie. IVC 28, 807\u2013813 (2010)","journal-title":"IVC"},{"issue":"5","key":"38_CR15","first-page":"597","volume":"12","author":"BK Gunturk","year":"2003","unstructured":"Gunturk, B.K., Batur, A.U., Altunbasak, Y., Hayes, M.H., Mersereau, R.M.: Eigenface-domain super-resolution for face recognition. IEEE TIP 12(5), 597\u2013606 (2003)","journal-title":"IEEE TIP"},{"key":"38_CR16","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1007\/978-3-319-46487-9_6","volume-title":"Computer Vision \u2013 ECCV 2016","author":"Y Guo","year":"2016","unstructured":"Guo, Y., Zhang, L., Hu, Y., He, X., Gao, J.: MS-Celeb-1M: a dataset and benchmark for large-scale face recognition. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9907, pp. 87\u2013102. Springer, Cham (2016). \n                      https:\/\/doi.org\/10.1007\/978-3-319-46487-9_6"},{"key":"38_CR17","unstructured":"He, X., Cai, D., Yan, S., Zhang, H.J.: Neighborhood preserving embedding. In: ICCV (2005)"},{"key":"38_CR18","doi-asserted-by":"crossref","unstructured":"Hennings-Yeomans, P.H., Baker, S., Kumar, B.V.: Simultaneous super-resolution and feature extraction for recognition of low-resolution faces. In: CVPR (2008)","DOI":"10.1109\/CVPR.2008.4587810"},{"key":"38_CR19","doi-asserted-by":"crossref","unstructured":"Hu, P., Ramanan, D.: Finding tiny faces. arXiv (2016)","DOI":"10.1109\/CVPR.2017.166"},{"key":"38_CR20","unstructured":"Huang, G.B., Ramesh, M., Berg, T., Learned-Miller, E.: Labeled faces in the wild: a database for studying face recognition in unconstrained environments. University of Massachusetts, Technical report (2007)"},{"issue":"1","key":"38_CR21","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1109\/TPAMI.2010.57","volume":"33","author":"H Jegou","year":"2011","unstructured":"Jegou, H., Douze, M., Schmid, C.: Product quantization for nearest neighbor search. IEEE TPAMI 33(1), 117\u2013128 (2011)","journal-title":"IEEE TPAMI"},{"key":"38_CR22","doi-asserted-by":"crossref","unstructured":"Kemelmacher-Shlizerman, I., Seitz, S.M., Miller, D., Brossard, E.: The MegaFace benchmark: 1 million faces for recognition at scale. In: CVPR (2016)","DOI":"10.1109\/CVPR.2016.527"},{"key":"38_CR23","doi-asserted-by":"crossref","unstructured":"Kim, J., Kwon Lee, J., Mu Lee, K.: Accurate image super-resolution using very deep convolutional networks. In: CVPR (2016)","DOI":"10.1109\/CVPR.2016.182"},{"key":"38_CR24","doi-asserted-by":"crossref","unstructured":"Klare, B.F., et al.: Pushing the frontiers of unconstrained face detection and recognition: IARPA Janus benchmark A. In: CVPR (2015)","DOI":"10.1109\/CVPR.2015.7298803"},{"key":"38_CR25","doi-asserted-by":"crossref","unstructured":"Lei, Z., Ahonen, T., Pietik\u00e4inen, M., Li, S.Z.: Local frequency descriptor for low-resolution face recognition. In: FG (2011)","DOI":"10.1109\/FG.2011.5771391"},{"key":"38_CR26","doi-asserted-by":"crossref","unstructured":"Liu, W., Wen, Y., Yu, Z., Li, M., Raj, B., Song, L.: SphereFace: deep hypersphere embedding for face recognition. arXiv (2017)","DOI":"10.1109\/CVPR.2017.713"},{"key":"38_CR27","doi-asserted-by":"crossref","unstructured":"Liu, Z., Luo, P., Wang, X., Tang, X.: Deep learning face attributes in the wild. In: ICCV (2015)","DOI":"10.1109\/ICCV.2015.425"},{"key":"38_CR28","doi-asserted-by":"crossref","unstructured":"Nech, A., Kemelmacher-Shlizerman, I.: Level playing field for million scale face recognition. arXiv preprint \n                      arXiv:1705.00393\n                      \n                     (2017)","DOI":"10.1109\/CVPR.2017.363"},{"key":"38_CR29","doi-asserted-by":"crossref","unstructured":"Ng, H.W., Winkler, S.: A data-driven approach to cleaning large face datasets. In: ICIP (2014)","DOI":"10.1109\/ICIP.2014.7025068"},{"key":"38_CR30","doi-asserted-by":"crossref","unstructured":"Parkhi, O.M., Vedaldi, A., Zisserman, A.: Deep face recognition. In: BMVC (2015)","DOI":"10.5244\/C.29.41"},{"issue":"5","key":"38_CR31","doi-asserted-by":"publisher","first-page":"831","DOI":"10.1109\/TPAMI.2009.59","volume":"32","author":"PJ Phillips","year":"2010","unstructured":"Phillips, P.J., et al.: FRVT 2006 and ICE 2006 large-scale experimental results. IEEE TPAMI 32(5), 831\u2013846 (2010)","journal-title":"IEEE TPAMI"},{"issue":"8","key":"38_CR32","first-page":"3770","volume":"21","author":"CX Ren","year":"2012","unstructured":"Ren, C.X., Dai, D.Q., Yan, H.: Coupled kernel embedding for low-resolution face image recognition. IEEE TIP 21(8), 3770\u20133783 (2012)","journal-title":"IEEE TIP"},{"key":"38_CR33","unstructured":"Samaria, F.S., Harter, A.C.: Parameterisation of a stochastic model for human face identification. In: IEEE Workshop on Applications of Computer Vision (1994)"},{"key":"38_CR34","doi-asserted-by":"crossref","unstructured":"Shekhar, S., Patel, V.M., Chellappa, R.: Synthesis-based recognition of low resolution faces. In: IJCB (2011)","DOI":"10.1109\/IJCB.2011.6117545"},{"key":"38_CR35","unstructured":"Sim, T., Baker, S., Bsat, M.: The CMU pose, illumination, and expression (PIE) database. In: FG, pp. 53\u201358 (2002)"},{"key":"38_CR36","unstructured":"Sun, Y., Chen, Y., Wang, X., Tang, X.: Deep learning face representation by joint identification-verification. In: NIPS (2014)"},{"key":"38_CR37","doi-asserted-by":"crossref","unstructured":"Tai, Y., Yang, J., Liu, X.: Image super-resolution via deep recursive residual network. In: CVPR (2017)","DOI":"10.1109\/CVPR.2017.298"},{"issue":"11","key":"38_CR38","doi-asserted-by":"publisher","first-page":"1958","DOI":"10.1109\/TPAMI.2008.128","volume":"30","author":"A Torralba","year":"2008","unstructured":"Torralba, A., Fergus, R., Freeman, W.T.: 80 million tiny images: a large data set for nonparametric object and scene recognition. IEEE TPAMI 30(11), 1958\u20131970 (2008)","journal-title":"IEEE TPAMI"},{"key":"38_CR39","doi-asserted-by":"publisher","first-page":"1122","DOI":"10.1109\/TPAMI.2016.2582166","volume":"39","author":"D Wang","year":"2016","unstructured":"Wang, D., Otto, C., Jain, A.K.: Face search at scale. IEEE TPAMI 39, 1122\u20131136 (2016)","journal-title":"IEEE TPAMI"},{"key":"38_CR40","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"486","DOI":"10.1007\/3-540-44887-X_58","volume-title":"Audio- and Video-Based Biometric Person Authentication","author":"X Wang","year":"2003","unstructured":"Wang, X., Tang, X.: Face hallucination and recognition. In: Kittler, J., Nixon, M.S. (eds.) AVBPA 2003. LNCS, vol. 2688, pp. 486\u2013494. Springer, Heidelberg (2003). \n                      https:\/\/doi.org\/10.1007\/3-540-44887-X_58"},{"key":"38_CR41","doi-asserted-by":"crossref","unstructured":"Wang, Z., Chang, S., Yang, Y., Liu, D., Huang, T.S.: Studying very low resolution recognition using deep networks. In: CVPR (2016)","DOI":"10.1109\/CVPR.2016.518"},{"key":"38_CR42","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"499","DOI":"10.1007\/978-3-319-46478-7_31","volume-title":"Computer Vision \u2013 ECCV 2016","author":"Y Wen","year":"2016","unstructured":"Wen, Y., Zhang, K., Li, Z., Qiao, Y.: A discriminative feature learning approach for deep face recognition. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9911, pp. 499\u2013515. Springer, Cham (2016). \n                      https:\/\/doi.org\/10.1007\/978-3-319-46478-7_31"},{"key":"38_CR43","doi-asserted-by":"crossref","unstructured":"Wong, Y., Sanderson, C., Mau, S., Lovell, B.C.: Dynamic amelioration of resolution mismatches for local feature based identity inference. In: ICPR (2010)","DOI":"10.1109\/ICPR.2010.299"},{"key":"38_CR44","doi-asserted-by":"crossref","unstructured":"Yang, S., Luo, P., Loy, C.C., Tang, X.: WIDER FACE: a face detection benchmark. In: CVPR (2016)","DOI":"10.1109\/CVPR.2016.596"},{"key":"38_CR45","unstructured":"Yi, D., Lei, Z., Liao, S., Li, S.Z.: Learning face representation from scratch. arXiv (2014)"},{"key":"38_CR46","doi-asserted-by":"crossref","unstructured":"Zhang, N., Paluri, M., Taigman, Y., Fergus, R., Bourdev, L.: Beyond frontal faces: improving person recognition using multiple cues. In: CVPR (2015)","DOI":"10.1109\/CVPR.2015.7299113"},{"key":"38_CR47","unstructured":"Zhu, X.: Semantic structure discovery in surveillance videos. Ph.D. thesis, Queen Mary University of London (2016)"},{"issue":"1","key":"38_CR48","first-page":"327","volume":"21","author":"WW Zou","year":"2012","unstructured":"Zou, W.W., Yuen, P.C.: Very low resolution face recognition problem. IEEE TIP 21(1), 327\u2013340 (2012)","journal-title":"IEEE TIP"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ACCV 2018"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-20893-6_38","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,28]],"date-time":"2019-05-28T03:58:19Z","timestamp":1559015899000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-20893-6_38"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030208929","9783030208936"],"references-count":48,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-20893-6_38","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"29 May 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ACCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Asian Conference on Computer Vision","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Perth, WA","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Australia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2 December 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 December 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"accv2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/accv2018.net\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"Microsoft CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"979","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"274","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"28% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"2.7","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}}]}}