{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T23:46:04Z","timestamp":1782949564987,"version":"3.54.5"},"publisher-location":"Cham","reference-count":43,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031936968","type":"print"},{"value":"9783031936975","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T00:00:00Z","timestamp":1753315200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T00:00:00Z","timestamp":1753315200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-3-031-93697-5_18","type":"book-chapter","created":{"date-parts":[[2025,7,23]],"date-time":"2025-07-23T13:48:33Z","timestamp":1753278513000},"page":"244-258","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Unconstrained Low-Resolution Face Recognition Using Attention Network and\u00a0Resolution Aware Images"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2665-7073","authenticated-orcid":false,"given":"Ravindra Kumar","family":"Soni","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0550-0376","authenticated-orcid":false,"given":"Neeta","family":"Nain","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,7,24]]},"reference":[{"key":"18_CR1","doi-asserted-by":"publisher","unstructured":"Cao, Q., Shen, L., Xie, W., Parkhi, O.M., Zisserman, A.: Vggface2: a dataset for recognising faces across pose and age. In: 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018), pp. 67\u201374. IEEE Computer Society, Los Alamitos, CA, USA (may 2018). https:\/\/doi.org\/10.1109\/FG.2018.00020, https:\/\/doi.ieeecomputersociety.org\/10.1109\/FG.2018.00020","DOI":"10.1109\/FG.2018.00020"},{"key":"18_CR2","unstructured":"Chen, T., et al.: Mxnet: a flexible and efficient machine learning library for heterogeneous distributed systems. arXiv preprint arXiv:1512.01274 (2015)"},{"key":"18_CR3","unstructured":"Cheng, Z., Zhu, X., Gong, S.: Surveillance face recognition challenge. arXiv preprint arXiv:1804.09691 (2018)"},{"key":"18_CR4","doi-asserted-by":"crossref","unstructured":"Cheng, Z., Zhu, X., Gong, S.: Low-resolution face recognition. In: Computer Vision\u2013ACCV 2018: 14th Asian Conference on Computer Vision, Perth, Australia, December 2\u20136, 2018, Revised Selected Papers, Part III 14. pp. 605\u2013621. Springer (2019)","DOI":"10.1007\/978-3-030-20893-6_38"},{"key":"18_CR5","doi-asserted-by":"crossref","unstructured":"Deng, J., Guo, J., Xue, N., Zafeiriou, S.: Arcface: additive angular margin loss for deep face recognition. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4690\u20134699 (2019)","DOI":"10.1109\/CVPR.2019.00482"},{"issue":"4","key":"18_CR6","doi-asserted-by":"publisher","first-page":"1002","DOI":"10.1109\/TPAMI.2017.2700390","volume":"40","author":"C Ding","year":"2017","unstructured":"Ding, C., Tao, D.: Trunk-branch ensemble convolutional neural networks for video-based face recognition. IEEE Trans. Pattern Anal. Mach. Intell. 40(4), 1002\u20131014 (2017)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"2","key":"18_CR7","doi-asserted-by":"publisher","first-page":"295","DOI":"10.1109\/TPAMI.2015.2439281","volume":"38","author":"C Dong","year":"2015","unstructured":"Dong, C., Loy, C.C., He, K., Tang, X.: Image super-resolution using deep convolutional networks. IEEE Trans. Pattern Anal. Mach. Intell. 38(2), 295\u2013307 (2015)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"18_CR8","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"741","DOI":"10.1007\/978-3-030-58555-6_44","volume-title":"Computer Vision \u2013 ECCV 2020","author":"H Fang","year":"2020","unstructured":"Fang, H., Deng, W., Zhong, Y., Hu, J.: Generate to Adapt: resolution adaption network for surveillance face recognition. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12360, pp. 741\u2013758. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58555-6_44"},{"key":"18_CR9","unstructured":"Gildenblat, J., contributors: Pytorch library for cam methods (2021). https:\/\/github.com\/jacobgil\/pytorch-grad-cam"},{"issue":"3","key":"18_CR10","doi-asserted-by":"publisher","first-page":"863","DOI":"10.1007\/s11042-009-0417-2","volume":"51","author":"M Grgic","year":"2011","unstructured":"Grgic, M., Delac, K., Grgic, S.: Scface-surveillance cameras face database. Multimedia Tools Appli. 51(3), 863\u2013879 (2011)","journal-title":"Multimedia Tools Appli."},{"key":"18_CR11","doi-asserted-by":"crossref","unstructured":"Guo, J., Zhu, X., Zhao, C., Cao, D., Lei, Z., Li, S.Z.: Learning meta face recognition in unseen domains. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 6163\u20136172 (2020)","DOI":"10.1109\/CVPR42600.2020.00620"},{"key":"18_CR12","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"issue":"8","key":"18_CR13","first-page":"2","volume":"14","author":"G Hinton","year":"2012","unstructured":"Hinton, G., Srivastava, N., Swersky, K.: Neural networks for machine learning lecture 6a overview of mini-batch gradient descent. Cited on 14(8), 2 (2012)","journal-title":"Cited on"},{"key":"18_CR14","doi-asserted-by":"crossref","unstructured":"Hu, J., Shen, L., Sun, G.: Squeeze-and-excitation networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 7132\u20137141 (2018)","DOI":"10.1109\/CVPR.2018.00745"},{"key":"18_CR15","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. Tech. Rep. 07-49, University of Massachusetts, Amherst (October 2007)"},{"key":"18_CR16","unstructured":"Knoche, M., H\u00f6rmann, S., Rigoll, G.: Image resolution susceptibility of face recognition models. CoRR abs\/ arXiv: 2107.03769 (2021)"},{"issue":"11","key":"18_CR17","doi-asserted-by":"publisher","first-page":"2278","DOI":"10.1109\/5.726791","volume":"86","author":"Y Lecun","year":"1998","unstructured":"Lecun, Y., Bottou, L., Bengio, Y., Haffner, P.: Gradient-based learning applied to document recognition. Proc. IEEE 86(11), 2278\u20132324 (1998). https:\/\/doi.org\/10.1109\/5.726791","journal-title":"Proc. IEEE"},{"key":"18_CR18","doi-asserted-by":"crossref","unstructured":"Ledig, C., et\u00a0al.: Photo-realistic single image super-resolution using a generative adversarial network. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4681\u20134690 (2017)","DOI":"10.1109\/CVPR.2017.19"},{"issue":"1","key":"18_CR19","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1109\/LSP.2009.2031705","volume":"17","author":"B Li","year":"2009","unstructured":"Li, B., Chang, H., Shan, S., Chen, X.: Low-resolution face recognition via coupled locality preserving mappings. IEEE Signal Process. Lett. 17(1), 20\u201323 (2009)","journal-title":"IEEE Signal Process. Lett."},{"key":"18_CR20","doi-asserted-by":"crossref","unstructured":"Lim, B., Son, S., Kim, H., Nah, S., Mu\u00a0Lee, K.: Enhanced deep residual networks for single image super-resolution. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 136\u2013144 (2017)","DOI":"10.1109\/CVPRW.2017.151"},{"key":"18_CR21","doi-asserted-by":"crossref","unstructured":"Liu, W., Wen, Y., Yu, Z., Li, M., Raj, B., Song, L.: Sphereface: deep hypersphere embedding for face recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 212\u2013220 (2017)","DOI":"10.1109\/CVPR.2017.713"},{"key":"18_CR22","unstructured":"Loffe, S., Normalization, C.: Accelerating deep network training by reducing internal covariate shift. arXiv (2014)"},{"issue":"4","key":"18_CR23","doi-asserted-by":"publisher","first-page":"526","DOI":"10.1109\/LSP.2018.2810121","volume":"25","author":"Z Lu","year":"2018","unstructured":"Lu, Z., Jiang, X., Kot, A.: Deep coupled resnet for low-resolution face recognition. IEEE Signal Process. Lett. 25(4), 526\u2013530 (2018)","journal-title":"IEEE Signal Process. Lett."},{"key":"18_CR24","doi-asserted-by":"crossref","unstructured":"Mart\u00ednez-D\u00edaz, Y., M\u00e9ndez-V\u00e1zquez, H., Luevano, L.S., Chang, L., Gonzalez-Mendoza, M.: Lightweight low-resolution face recognition for surveillance applications. In: 2020 25th International Conference on Pattern Recognition (ICPR), pp. 5421\u20135428. IEEE (2021)","DOI":"10.1109\/ICPR48806.2021.9412280"},{"key":"18_CR25","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2020.103927","volume":"99","author":"FV Massoli","year":"2020","unstructured":"Massoli, F.V., Amato, G., Falchi, F.: Cross-resolution learning for face recognition. Image Vis. Comput. 99, 103927 (2020)","journal-title":"Image Vis. Comput."},{"key":"18_CR26","doi-asserted-by":"crossref","unstructured":"Parkhi, O.M., Vedaldi, A., Zisserman, A.: Deep face recognition (2015)","DOI":"10.5244\/C.29.41"},{"key":"18_CR27","doi-asserted-by":"crossref","unstructured":"Schroff, F., Kalenichenko, D., Philbin, J.: Facenet: a unified embedding for face recognition and clustering. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 815\u2013823 (2015)","DOI":"10.1109\/CVPR.2015.7298682"},{"key":"18_CR28","doi-asserted-by":"publisher","unstructured":"Shin, S., Lee, J., Lee, J., Yu, Y., Lee, K.: Teaching where to look: attention similarity knowledge distillation for low resolution face recognition. In: European Conference on Computer Vision, pp. 631\u2013647. Springer (2022). https:\/\/doi.org\/10.1007\/978-3-031-19775-8_37","DOI":"10.1007\/978-3-031-19775-8_37"},{"key":"18_CR29","doi-asserted-by":"publisher","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition (2014). https:\/\/doi.org\/10.48550\/ARXIV.1409.1556","DOI":"10.48550\/ARXIV.1409.1556"},{"key":"18_CR30","unstructured":"Sun, Y., Chen, Y., Wang, X., Tang, X.: Deep learning face representation by joint identification-verification. In: Proceedings of the 27th International Conference on Neural Information Processing Systems, NIPS 2014, vol. 2, pp. 1988\u20131996. MIT Press, Cambridge (2014)"},{"issue":"11","key":"18_CR31","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 Trans. Pattern Anal. Mach. Intell. 30(11), 1958\u20131970 (2008). https:\/\/doi.org\/10.1109\/TPAMI.2008.128","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"18_CR32","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1007\/978-3-030-11021-5_5","volume-title":"Computer Vision \u2013 ECCV 2018 Workshops","author":"X Wang","year":"2019","unstructured":"Wang, X., et al.: ESRGAN: enhanced super-resolution generative adversarial networks. In: Leal-Taix\u00e9, L., Roth, S. (eds.) ECCV 2018. LNCS, vol. 11133, pp. 63\u201379. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-11021-5_5"},{"key":"18_CR33","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, Yu.: 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). https:\/\/doi.org\/10.1007\/978-3-319-46478-7_31"},{"key":"18_CR34","doi-asserted-by":"crossref","unstructured":"Wolf, L., Hassner, T., Maoz, I.: Face recognition in unconstrained videos with matched background similarity. In: CVPR 2011, pp. 529\u2013534. IEEE (2011)","DOI":"10.1109\/CVPR.2011.5995566"},{"key":"18_CR35","doi-asserted-by":"publisher","unstructured":"Wolf, L., Hassner, T., Maoz, I.: Face recognition in unconstrained videos with matched background similarity. In: CVPR 2011, pp. 529\u2013534 (2011). https:\/\/doi.org\/10.1109\/CVPR.2011.5995566","DOI":"10.1109\/CVPR.2011.5995566"},{"key":"18_CR36","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/978-3-030-01234-2_1","volume-title":"Computer Vision \u2013 ECCV 2018","author":"S Woo","year":"2018","unstructured":"Woo, S., Park, J., Lee, J.-Y., Kweon, I.S.: CBAM: convolutional block attention module. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11211, pp. 3\u201319. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01234-2_1"},{"issue":"11","key":"18_CR37","doi-asserted-by":"publisher","first-page":"2884","DOI":"10.1109\/TIFS.2018.2833032","volume":"13","author":"X Wu","year":"2018","unstructured":"Wu, X., He, R., Sun, Z., Tan, T.: A light CNN for deep face representation with noisy labels. IEEE Trans. Inf. Forensics Secur. 13(11), 2884\u20132896 (2018)","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"issue":"11","key":"18_CR38","doi-asserted-by":"publisher","first-page":"2861","DOI":"10.1109\/TIP.2010.2050625","volume":"19","author":"J Yang","year":"2010","unstructured":"Yang, J., Wright, J., Huang, T.S., Ma, Y.: Image super-resolution via sparse representation. IEEE Trans. Image Process. 19(11), 2861\u20132873 (2010)","journal-title":"IEEE Trans. Image Process."},{"key":"18_CR39","unstructured":"Yi, D., Lei, Z., Liao, S., Li, S.Z.: Learning face representation from scratch. arXiv preprint arXiv:1411.7923 (2014)"},{"key":"18_CR40","doi-asserted-by":"crossref","unstructured":"Yin, X., Tai, Y., Huang, Y., Liu, X.: Fan: feature adaptation network for surveillance face recognition and normalization. In: Proceedings of the Asian Conference on Computer Vision (2020)","DOI":"10.1007\/978-3-030-69532-3_19"},{"key":"18_CR41","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"219","DOI":"10.1007\/978-3-030-01240-3_14","volume-title":"Computer Vision \u2013 ECCV 2018","author":"X Yu","year":"2018","unstructured":"Yu, X., Fernando, B., Ghanem, B., Porikli, F., Hartley, R.: Face super-resolution guided by facial component heatmaps. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11213, pp. 219\u2013235. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01240-3_14"},{"key":"18_CR42","doi-asserted-by":"publisher","unstructured":"Zangeneh, E., Rahmati, M., Mohsenzadeh, Y.: Low resolution face recognition using a two-branch deep convolutional neural network architecture. Expert Syst. Appli. 139, 112854 (2020). https:\/\/doi.org\/10.1016\/j.eswa.2019.112854, https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0957417419305561","DOI":"10.1016\/j.eswa.2019.112854"},{"key":"18_CR43","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/978-3-030-01252-6_1","volume-title":"Computer Vision \u2013 ECCV 2018","author":"C Chen","year":"2018","unstructured":"Chen, C., Xiong, Z., Tian, X., Wu, F.: Deep boosting for image denoising. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11215, pp. 3\u201319. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-030-01252-6_1"}],"container-title":["Communications in Computer and Information Science","Computer Vision and Image Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-93697-5_18","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T23:28:23Z","timestamp":1782948503000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-93697-5_18"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,24]]},"ISBN":["9783031936968","9783031936975"],"references-count":43,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-93697-5_18","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"value":"1865-0929","type":"print"},{"value":"1865-0937","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,7,24]]},"assertion":[{"value":"24 July 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CVIP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computer Vision and Image Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chennai","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"India","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 December 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 December 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cvip2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/cvip2024.iiitdm.ac.in\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}