{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,28]],"date-time":"2025-05-28T04:16:04Z","timestamp":1748405764871,"version":"3.41.0"},"publisher-location":"Cham","reference-count":33,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031919060","type":"print"},{"value":"9783031919077","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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":[[2025]]},"DOI":"10.1007\/978-3-031-91907-7_21","type":"book-chapter","created":{"date-parts":[[2025,5,27]],"date-time":"2025-05-27T15:46:03Z","timestamp":1748360763000},"page":"351-367","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["How Knowledge Distillation Mitigates the\u00a0Synthetic Gap in\u00a0Fair Face Recognition"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1333-4889","authenticated-orcid":false,"given":"Pedro C.","family":"Neto","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1603-9458","authenticated-orcid":false,"given":"Ivona","family":"Colakovic","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4441-9690","authenticated-orcid":false,"given":"Sa\u0161o","family":"Karakati\u010d","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6685-2033","authenticated-orcid":false,"given":"Ana F.","family":"Sequeira","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,5,12]]},"reference":[{"key":"21_CR1","doi-asserted-by":"publisher","unstructured":"Atzori, A., Boutros, F., Damer, N., Fenu, G., Marras, M.: If it\u2019s not enough, make it so: reducing authentic data demand in face recognition through synthetic faces. CoRR arXiv:2404.03537 (2024). https:\/\/doi.org\/10.48550\/ARXIV.2404.03537","DOI":"10.48550\/ARXIV.2404.03537"},{"key":"21_CR2","doi-asserted-by":"publisher","unstructured":"Babnik, Z., Boutros, F., Damer, N., Peer, P., Struc, V.: AI-KD: towards alignment invariant face image quality assessment using knowledge distillation. CoRR arXiv:2404.09555 (2024). https:\/\/doi.org\/10.48550\/ARXIV.2404.09555","DOI":"10.48550\/ARXIV.2404.09555"},{"key":"21_CR3","doi-asserted-by":"publisher","unstructured":"Bae, G., et al.: Digiface-1M: 1 Million digital face images for face recognition. In: IEEE\/CVF Winter Conference on Applications of Computer Vision, WACV 2023, Waikoloa, HI, USA, January 2\u20137, 2023, pp. 3515\u20133524. IEEE (2023). https:\/\/doi.org\/10.1109\/WACV56688.2023.00352","DOI":"10.1109\/WACV56688.2023.00352"},{"key":"21_CR4","doi-asserted-by":"crossref","unstructured":"Boutros, F., Damer, N., Kirchbuchner, F., Kuijper, A.: Elasticface: elastic margin loss for deep face recognition. In: CVPR Workshops, pp. 1577\u20131586. IEEE (2022)","DOI":"10.1109\/CVPRW56347.2022.00164"},{"key":"21_CR5","doi-asserted-by":"crossref","unstructured":"Boutros, F., Grebe, J.H., Kuijper, A., Damer, N.: Idiff-face: synthetic-based face recognition through fizzy identity-conditioned diffusion models. In: ICCV, pp. 19593\u201319604. IEEE (2023)","DOI":"10.1109\/ICCV51070.2023.01800"},{"key":"21_CR6","doi-asserted-by":"crossref","unstructured":"Boutros, F., Huber, M., Siebke, P., Rieber, T., Damer, N.: Sface: privacy-friendly and accurate face recognition using synthetic data. In: IJCB, pp. 1\u201311. IEEE (2022)","DOI":"10.1109\/IJCB54206.2022.10007961"},{"key":"21_CR7","doi-asserted-by":"publisher","unstructured":"Boutros, F., Klemt, M., Fang, M., Kuijper, A., Damer, N.: ExfaceGAN: exploring identity directions in GAN\u2019s learned latent space for synthetic identity generation. In: IEEE International Joint Conference on Biometrics, IJCB 2023, Ljubljana, Slovenia, September 25\u201328, 2023, pp. 1\u201310. IEEE (2023). https:\/\/doi.org\/10.1109\/IJCB57857.2023.10449036","DOI":"10.1109\/IJCB57857.2023.10449036"},{"key":"21_CR8","doi-asserted-by":"publisher","unstructured":"Boutros, F., et al.: PocketNet: extreme lightweight face recognition network using neural architecture search and multistep knowledge distillation. IEEE Access 10, 46823\u201346833 (2022). https:\/\/doi.org\/10.1109\/ACCESS.2022.3170561","DOI":"10.1109\/ACCESS.2022.3170561"},{"key":"21_CR9","doi-asserted-by":"crossref","unstructured":"Boutros, F., \u0160truc, V., Damer, N.: Adadistill: adaptive knowledge distillation for deep face recognition. In: ECCV (2024)","DOI":"10.1007\/978-3-031-73001-6_10"},{"key":"21_CR10","doi-asserted-by":"publisher","unstructured":"Boutros, F., Struc, V., Fi\u00e9rrez, J., Damer, N.: Synthetic data for face recognition: current state and future prospects. Image Vis. Comput. 135, 104688 (2023). https:\/\/doi.org\/10.1016\/j.imavis.2023.104688","DOI":"10.1016\/j.imavis.2023.104688"},{"key":"21_CR11","doi-asserted-by":"crossref","unstructured":"Caldeira, E., Neto, P.C., Huber, M., Damer, N., Sequeira, A.F.: Model compression techniques in biometrics applications: a survey. CoRR arXiv:2401.10139 (2024)","DOI":"10.1016\/j.inffus.2024.102657"},{"key":"21_CR12","doi-asserted-by":"crossref","unstructured":"Chen, S., Liu, Y., Gao, X., Han, Z.: Mobilefacenets: efficient CNNs for accurate real-time face verification on mobile devices. In: CCBR. Lecture Notes in Computer Science, vol. 10996, pp. 428\u2013438. Springer (2018)","DOI":"10.1007\/978-3-319-97909-0_46"},{"key":"21_CR13","unstructured":"DeAndres-Tame, I., et\u00a0al.: FRCSYN challenge at CVPR 2024: face recognition challenge in the era of synthetic data. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3173\u20133183 (2024)"},{"key":"21_CR14","doi-asserted-by":"crossref","unstructured":"Deng, J., Guo, J., Xue, N., Zafeiriou, S.: Arcface: additive angular margin loss for deep face recognition. In: CVPR, pp. 4690\u20134699. Computer Vision Foundation \/ IEEE (2019)","DOI":"10.1109\/CVPR.2019.00482"},{"key":"21_CR15","unstructured":"Dhar, P., Gleason, J., Roy, A., Castillo, C.D., Phillips, P.J., Chellappa, R.: Distill and de-bias: mitigating bias in face recognition using knowledge distillation. CoRR arXiv:2112.09786 (2021)."},{"key":"21_CR16","doi-asserted-by":"crossref","unstructured":"Guo, Y., Zhang, L., Hu, Y., He, X., Gao, J.: Ms-celeb-1M: a dataset and benchmark for large-scale face recognition. In: ECCV (3). Lecture Notes in Computer Science, vol.\u00a09907, pp. 87\u2013102. Springer (2016)","DOI":"10.1007\/978-3-319-46487-9_6"},{"key":"21_CR17","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: CVPR, pp. 770\u2013778. IEEE Computer Society (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"21_CR18","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":"21_CR19","doi-asserted-by":"publisher","unstructured":"Huang, Y., Wu, J., Xu, X., Ding, S.: Evaluation-oriented knowledge distillation for deep face recognition. In: IEEE\/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2022, New Orleans, LA, USA, June 18\u201324, 2022, pp. 18719\u201318728. IEEE (2022). https:\/\/doi.org\/10.1109\/CVPR52688.2022.01818","DOI":"10.1109\/CVPR52688.2022.01818"},{"key":"21_CR20","doi-asserted-by":"publisher","unstructured":"Jung, S., Lee, D., Park, T., Moon, T.: Fair feature distillation for visual recognition. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2021, virtual, June 19\u201325, 2021, pp. 12115\u201312124. Computer Vision Foundation \/ IEEE (2021). https:\/\/doi.org\/10.1109\/CVPR46437.2021.01194, https:\/\/openaccess.thecvf.com\/content\/CVPR2021\/html\/Jung_Fair_Feature_Distillation_for_Visual_Recognition_CVPR_2021_paper.html","DOI":"10.1109\/CVPR46437.2021.01194"},{"key":"21_CR21","doi-asserted-by":"crossref","unstructured":"Kim, M., Jain, A.K., Liu, X.: Adaface: quality adaptive margin for face recognition. In: CVPR, pp. 18729\u201318738. IEEE (2022)","DOI":"10.1109\/CVPR52688.2022.01819"},{"key":"21_CR22","doi-asserted-by":"crossref","unstructured":"Kim, M., Liu, F., Jain, A.K., Liu, X.: DCFace: synthetic face generation with dual condition diffusion model. In: CVPR, pp. 12715\u201312725. IEEE (2023)","DOI":"10.1109\/CVPR52729.2023.01223"},{"key":"21_CR23","doi-asserted-by":"publisher","unstructured":"Liu, B., Zhang, S., Song, G., You, H., Liu, Y.: Rectifying the data bias in knowledge distillation. In: IEEE\/CVF International Conference on Computer Vision Workshops, ICCVW 2021, Montreal, BC, Canada, October 11\u201317, 2021, pp. 1477\u20131486. IEEE (2021). https:\/\/doi.org\/10.1109\/ICCVW54120.2021.00171","DOI":"10.1109\/ICCVW54120.2021.00171"},{"key":"21_CR24","doi-asserted-by":"crossref","unstructured":"Moschoglou, S., Papaioannou, A., Sagonas, C., Deng, J., Kotsia, I., Zafeiriou, S.: Agedb: the first manually collected, in-the-wild age database. In: CVPR Workshops, pp. 1997\u20132005. IEEE Computer Society (2017)","DOI":"10.1109\/CVPRW.2017.250"},{"key":"21_CR25","doi-asserted-by":"publisher","unstructured":"Neto, P.C., Caldeira, E., Cardoso, J.S., Sequeira, A.F.: Compressed models decompress race biases: what quantized models forget for fair face recognition. In: Damer, N., et al. (eds.) International Conference of the Biometrics Special Interest Group, BIOSIG 2023, Darmstadt, Germany, September 20\u201322, 2023, pp.\u00a01\u20135. IEEE (2023). https:\/\/doi.org\/10.1109\/BIOSIG58226.2023.10346003","DOI":"10.1109\/BIOSIG58226.2023.10346003"},{"key":"21_CR26","unstructured":"Neto, P.C., Damer, N., Cardoso, J.S., Sequeira, A.F.: Beyond black and white: a more nuanced approach to facial recognition with continuous ethnicity. arxiv (2024)"},{"key":"21_CR27","unstructured":"Otroshi-Shahreza, H., et al.: SDFR: synthetic data for face recognition competition. CoRR arXiv:2404.04580 (2024)"},{"key":"21_CR28","doi-asserted-by":"publisher","unstructured":"Otroshi-Shahreza, H., George, A., Marcel, S.: Synthdistill: face recognition with knowledge distillation from synthetic data. In: IEEE International Joint Conference on Biometrics, IJCB 2023, Ljubljana, Slovenia, September 25\u201328, 2023, pp. 1\u201310. IEEE (2023). https:\/\/doi.org\/10.1109\/IJCB57857.2023.10448642","DOI":"10.1109\/IJCB57857.2023.10448642"},{"key":"21_CR29","doi-asserted-by":"crossref","unstructured":"Sengupta, S., Chen, J., Castillo, C.D., Patel, V.M., Chellappa, R., Jacobs, D.W.: Frontal to profile face verification in the wild. In: WACV, pp.\u00a01\u20139. IEEE Computer Society (2016)","DOI":"10.1109\/WACV.2016.7477558"},{"key":"21_CR30","doi-asserted-by":"crossref","unstructured":"Wang, M., Deng, W., Hu, J., Tao, X., Huang, Y.: Racial faces in the wild: reducing racial bias by information maximization adaptation network. In: ICCV, pp. 692\u2013702. IEEE (2019)","DOI":"10.1109\/ICCV.2019.00078"},{"issue":"11","key":"21_CR31","first-page":"8433","volume":"44","author":"M Wang","year":"2022","unstructured":"Wang, M., Zhang, Y., Deng, W.: Meta balanced network for fair face recognition. IEEE Trans. Pattern Anal. Mach. Intell. 44(11), 8433\u20138448 (2022)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"21_CR32","unstructured":"Zheng, T., Deng, W.: Cross-pose LFW: a database for studying cross-pose face recognition in unconstrained environments. Beijing Univ. Posts Telecommun. Tech. Rep 5(7), 5 (2018)"},{"key":"21_CR33","unstructured":"Zheng, T., Deng, W., Hu, J.: Cross-age LFW: a database for studying cross-age face recognition in unconstrained environments. CoRR arXiv:1708.08197 (2017)"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ECCV 2024 Workshops"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-91907-7_21","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,27]],"date-time":"2025-05-27T15:46:12Z","timestamp":1748360772000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-91907-7_21"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031919060","9783031919077"],"references-count":33,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-91907-7_21","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"12 May 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Computer Vision","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Milan","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","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":"29 September 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"eccv2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/eccv2024.ecva.net\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}