{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,25]],"date-time":"2026-07-25T01:44:40Z","timestamp":1784943880080,"version":"3.55.0"},"reference-count":112,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2024,1,20]],"date-time":"2024-01-20T00:00:00Z","timestamp":1705708800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,20]],"date-time":"2024-01-20T00:00:00Z","timestamp":1705708800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61806071"],"award-info":[{"award-number":["61806071"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62102129"],"award-info":[{"award-number":["62102129"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003787","name":"Natural Science Foundation of Hebei Province","doi-asserted-by":"publisher","award":["F2019202381"],"award-info":[{"award-number":["F2019202381"]}],"id":[{"id":"10.13039\/501100003787","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003787","name":"Natural Science Foundation of Hebei Province","doi-asserted-by":"publisher","award":["F2019202464"],"award-info":[{"award-number":["F2019202464"]}],"id":[{"id":"10.13039\/501100003787","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2024,3]]},"DOI":"10.1007\/s00521-023-09376-1","type":"journal-article","created":{"date-parts":[[2024,1,20]],"date-time":"2024-01-20T19:02:14Z","timestamp":1705777334000},"page":"4537-4561","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Age transformation based on deep learning: a survey"],"prefix":"10.1007","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3239-3086","authenticated-orcid":false,"given":"Yingchun","family":"Guo","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin","family":"Su","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gang","family":"Yan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ye","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xueqi","family":"Lv","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,1,20]]},"reference":[{"issue":"4","key":"9376_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3450626.3459805","volume":"40","author":"Y Alaluf","year":"2021","unstructured":"Alaluf Y, Patashnik O, Cohen-Or D (2021) Only a matter of style: age transformation using a style-based regression model. ACM Trans Graph (TOG) 40(4):1\u201312","journal-title":"ACM Trans Graph (TOG)"},{"issue":"1","key":"9376_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.forsciint.2007.03.015","volume":"172","author":"AM Albert","year":"2007","unstructured":"Albert AM, Ricanek K Jr, Patterson E (2007) A review of the literature on the aging adult skull and face: implications for forensic science research and applications. Forensic Sci Int 172(1):1\u20139","journal-title":"Forensic Sci Int"},{"key":"9376_CR3","doi-asserted-by":"publisher","DOI":"10.4324\/9780203771372","volume-title":"Social and applied aspects of perceiving faces","author":"TR Alley","year":"2013","unstructured":"Alley TR (2013) Social and applied aspects of perceiving faces. Psychology Press, London"},{"key":"9376_CR4","doi-asserted-by":"crossref","unstructured":"Antipov G, Baccouche M, Dugelay JL (2017) Face aging with conditional generative adversarial networks. In: 2017 IEEE international conference on image processing (ICIP), IEEE, pp 2089\u20132093","DOI":"10.1109\/ICIP.2017.8296650"},{"key":"9376_CR5","doi-asserted-by":"crossref","unstructured":"Bando Y, Kuratate T, Nishita T (2002) A simple method for modeling wrinkles on human skin. In: Proceedings of the 10th pacific conference on computer graphics and applications, 2002. IEEE, pp 166\u2013175","DOI":"10.1109\/PCCGA.2002.1167852"},{"key":"9376_CR6","doi-asserted-by":"crossref","unstructured":"Banerjee S, Mittal G, Joshi A, et\u00a0al (2023) Identity-preserving aging of face images via latent diffusion models. arXiv:2307.08585","DOI":"10.1109\/IJCB57857.2023.10448860"},{"issue":"108","key":"9376_CR7","first-page":"244","volume":"122","author":"G Baykal","year":"2022","unstructured":"Baykal G, Ozcelik F, Unal G (2022) Exploring deshufflegans in self-supervised generative adversarial networks. Pattern Recognit 122(108):244","journal-title":"Pattern Recognit"},{"key":"9376_CR8","unstructured":"Berg AC, Justo SC (2003) Aging of orbicularis muscle in virtual human faces. In: Proceedings on 7th international conference on information visualization, 2003. IV 2003. IEEE, pp 164\u2013168"},{"key":"9376_CR9","unstructured":"Bi\u0144kowski M, Sutherland D, Arbel M, et\u00a0al (2018) Demystifying mmd gans. ICLR"},{"issue":"6","key":"9376_CR10","first-page":"2975","volume":"34","author":"L Boussaad","year":"2022","unstructured":"Boussaad L, Boucetta A (2022) Deep-learning based descriptors in application to aging problem in face recognition. J King Saud Univ Comput Inf Sci 34(6):2975\u20132981","journal-title":"J King Saud Univ Comput Inf Sci"},{"issue":"108","key":"9376_CR11","first-page":"761","volume":"129","author":"PK Chandaliya","year":"2022","unstructured":"Chandaliya PK, Nain N (2022) Childgan: face aging and rejuvenation to find missing children. Pattern Recognit 129(108):761","journal-title":"Pattern Recognit"},{"issue":"3","key":"9376_CR12","doi-asserted-by":"publisher","first-page":"2811","DOI":"10.1007\/s00521-022-07721-4","volume":"35","author":"PK Chandaliya","year":"2023","unstructured":"Chandaliya PK, Nain N (2023) AW-GAN: face aging and rejuvenation using attention with wavelet GAN. Neural Comput Appl 35(3):2811\u20132825","journal-title":"Neural Comput Appl"},{"key":"9376_CR13","unstructured":"Chandaliya PK, Sinha A, Nain N (2020) Childface: Gender aware child face aging. In: 2020 International conference of the biometrics special interest group (BIOSIG). IEEE, pp 1\u20135"},{"key":"9376_CR14","doi-asserted-by":"crossref","unstructured":"Chen BC, Chen CS, Hsu WH (2014) Cross-age reference coding for age-invariant face recognition and retrieval. In: Computer vision\u2013ECCV 2014: 13th European conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part VI 13, Springer, pp 768\u2013783","DOI":"10.1007\/978-3-319-10599-4_49"},{"issue":"5","key":"9376_CR15","doi-asserted-by":"publisher","first-page":"1747","DOI":"10.1109\/TNNLS.2019.2927224","volume":"31","author":"K Chen","year":"2019","unstructured":"Chen K, Yao L, Zhang D et al (2019) A semisupervised recurrent convolutional attention model for human activity recognition. IEEE Trans Neural Netw Learn Syst 31(5):1747\u20131756","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"9376_CR16","unstructured":"Chen X, Lathuili\u00e8re S (2023) Face aging via diffusion-based editing. arXiv:2309.11321"},{"key":"9376_CR17","doi-asserted-by":"publisher","DOI":"10.14569\/ijacsa.2021.0121111","author":"HA Dahlan","year":"2021","unstructured":"Dahlan HA (2021) A survey on deep learning face age estimation model: method and ethnicity. Int J Adv Comput Sci Appl. https:\/\/doi.org\/10.14569\/ijacsa.2021.0121111","journal-title":"Int J Adv Comput Sci Appl"},{"key":"9376_CR18","doi-asserted-by":"crossref","unstructured":"Deb D, Aggarwal D, Jain AK (2021) Identifying missing children: face age-progression via deep feature aging. In: 2020 25th international conference on pattern recognition (ICPR). IEEE, pp 10,540\u201310,547","DOI":"10.1109\/ICPR48806.2021.9411913"},{"key":"9376_CR19","doi-asserted-by":"crossref","unstructured":"Deshmukh T, Kokate D (2022) Human face aging based on deep learning: a survey. Available at SSRN 4043509","DOI":"10.2139\/ssrn.4043509"},{"key":"9376_CR20","doi-asserted-by":"crossref","unstructured":"Despois J, Flament F, Perrot M (2020) AgingMapGAN (AMGAN): high-resolution controllable face aging with spatially-aware conditional GANs. In: Computer vision\u2013ECCV 2020 workshops: glasgow, UK, August 23\u201328, 2020, Proceedings, Part III 16. Springer, pp 613\u2013628","DOI":"10.1007\/978-3-030-67070-2_37"},{"issue":"12","key":"9376_CR21","doi-asserted-by":"publisher","first-page":"2170","DOI":"10.1109\/TIFS.2014.2359646","volume":"9","author":"E Eidinger","year":"2014","unstructured":"Eidinger E, Enbar R, Hassner T (2014) Age and gender estimation of unfiltered faces. IEEE Trans Inf Forensics Secur 9(12):2170\u20132179","journal-title":"IEEE Trans Inf Forensics Secur"},{"key":"9376_CR22","doi-asserted-by":"crossref","unstructured":"Fang H, Deng W, Zhong Y, et\u00a0al (2020) Triple-GAN: progressive face aging with triple translation loss. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition workshops, pp 804\u2013805","DOI":"10.1109\/CVPRW50498.2020.00410"},{"key":"9376_CR23","unstructured":"Fu Y (2014) Fg-net aging database. https:\/\/yanweifu.github.io\/FG_NET_data"},{"key":"9376_CR24","doi-asserted-by":"crossref","unstructured":"Fu Y, Xu Y, Huang TS (2007) Estimating human age by manifold analysis of face pictures and regression on aging features. In: 2007 IEEE international conference on multimedia and expo. IEEE, pp 1383\u20131386","DOI":"10.1109\/ICME.2007.4284917"},{"issue":"11","key":"9376_CR25","doi-asserted-by":"publisher","first-page":"1955","DOI":"10.1109\/TPAMI.2010.36","volume":"32","author":"Y Fu","year":"2010","unstructured":"Fu Y, Guo G, Huang TS (2010) Age synthesis and estimation via faces: a survey. IEEE Trans Pattern Anal Mach Intell 32(11):1955\u20131976","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"9376_CR26","unstructured":"Gandhi MR (2004) A method for automatic synthesis of aged human facial images. PhD thesis, McGill University, Montreal, Canada"},{"key":"9376_CR27","doi-asserted-by":"crossref","unstructured":"Gomez-Trenado G, Lathuili\u00e8re S, Mesejo P et al (2022) Custom structure preservation in face aging. In: Computer vision\u2014ECCV 2022: 17th European conference, Tel Aviv, Israel, October 23\u201327, 2022, Proceedings, Part XVI. Springer, pp 565\u2013580","DOI":"10.1007\/978-3-031-19787-1_32"},{"key":"9376_CR28","unstructured":"Goodfellow I, Pouget-Abadie J, Mirza M, et\u00a0al (2014) Generative adversarial nets. In: Ghahramani Z, Welling M, Cortes C, et\u00a0al (eds), Advances in neural information processing systems, vol\u00a027. Curran Associates, Inc., https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2014\/file\/5ca3e9b122f61f8f06494c97b1afccf3-Paper.pdf"},{"key":"9376_CR29","doi-asserted-by":"publisher","first-page":"83,376","DOI":"10.1109\/ACCESS.2021.3085835","volume":"9","author":"M Grimmer","year":"2021","unstructured":"Grimmer M, Ramachandra R, Busch C (2021) Deep face age progression: a survey. IEEE Access 9:83,376-83,393","journal-title":"IEEE Access"},{"key":"9376_CR30","unstructured":"Gulrajani I, Ahmed F, Arjovsky M, et\u00a0al (2017) Improved training of wasserstein gans. In: Advances in neural information processing systems, vol 30"},{"key":"9376_CR31","doi-asserted-by":"crossref","unstructured":"Guo G, Fu Y, Huang TS, et\u00a0al (2008) Locally adjusted robust regression for human age estimation. In: 2008 IEEE workshop on applications of computer vision, IEEE, pp 1\u20136","DOI":"10.1109\/WACV.2008.4544009"},{"key":"9376_CR32","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S, et\u00a0al (2016) Deep residual learning for image recognition. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 770\u2013778","DOI":"10.1109\/CVPR.2016.90"},{"key":"9376_CR33","doi-asserted-by":"crossref","unstructured":"He S, Liao W, Yang MY, et\u00a0al (2021) Disentangled lifespan face synthesis. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp 3877\u20133886","DOI":"10.1109\/ICCV48922.2021.00385"},{"key":"9376_CR34","unstructured":"Heusel M, Ramsauer H, Unterthiner T, et\u00a0al (2017) Gans trained by a two time-scale update rule converge to a local nash equilibrium. In: Advances in neural information processing systems, vol 30"},{"key":"9376_CR35","first-page":"6840","volume":"33","author":"J Ho","year":"2020","unstructured":"Ho J, Jain A, Abbeel P (2020) Denoising diffusion probabilistic models. Adv Neural Inf Process Syst 33:6840\u20136851","journal-title":"Adv Neural Inf Process Syst"},{"key":"9376_CR36","doi-asserted-by":"crossref","unstructured":"Hore A, Ziou D (2010) Image quality metrics: PSNR vs. SSIM. In: 2010 20th international conference on pattern recognition, IEEE, pp 2366\u20132369","DOI":"10.1109\/ICPR.2010.579"},{"issue":"3","key":"9376_CR37","first-page":"183","volume":"4","author":"WB Horng","year":"2001","unstructured":"Horng WB, Lee CP, Chen CW et al (2001) Classification of age groups based on facial features. J Appl Sci Eng 4(3):183\u2013192","journal-title":"J Appl Sci Eng"},{"key":"9376_CR38","doi-asserted-by":"crossref","unstructured":"Hsu GS, Xie RC, Chen ZT, et\u00a0al (2022) Agetransgan for facial age transformation with rectified performance metrics. In: European conference on computer vision. Springer, pp 580\u2013595","DOI":"10.1007\/978-3-031-19775-8_34"},{"key":"9376_CR39","doi-asserted-by":"crossref","unstructured":"Huang X, Belongie S (2017) Arbitrary style transfer in real-time with adaptive instance normalization. In: Proceedings of the IEEE international conference on computer vision, pp 1501\u20131510","DOI":"10.1109\/ICCV.2017.167"},{"key":"9376_CR40","doi-asserted-by":"crossref","unstructured":"Huang X, Gong M (2022) Landmark-guided conditional gans for face aging. In: Image analysis and processing\u2013ICIAP 2022: 21st international conference, Lecce, Italy, May 23\u201327, 2022, Proceedings, Part I. Springer, pp 270\u2013283","DOI":"10.1007\/978-3-031-06427-2_23"},{"key":"9376_CR41","doi-asserted-by":"publisher","first-page":"2031","DOI":"10.1109\/TIFS.2020.3047753","volume":"16","author":"Z Huang","year":"2020","unstructured":"Huang Z, Chen S, Zhang J et al (2020) PFA-GAN: progressive face aging with generative adversarial network. IEEE Trans Inf Forensics Secur 16:2031\u20132045","journal-title":"IEEE Trans Inf Forensics Secur"},{"key":"9376_CR42","doi-asserted-by":"crossref","unstructured":"Huang Z, Zhang J, Shan H (2021) When age-invariant face recognition meets face age synthesis: a multi-task learning framework. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 7282\u20137291","DOI":"10.1109\/CVPR46437.2021.00720"},{"key":"9376_CR43","doi-asserted-by":"crossref","unstructured":"Jeon S, Lee P, Hong K et al (2021) Continuous face aging generative adversarial networks. In: ICASSP 2021-2021 IEEE international conference on acoustics. Speech and signal processing (ICASSP). IEEE, pp 1995\u20131999","DOI":"10.1109\/ICASSP39728.2021.9414429"},{"key":"9376_CR44","doi-asserted-by":"crossref","unstructured":"Karras T, Laine S, Aila T (2019) A style-based generator architecture for generative adversarial networks. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 4401\u20134410","DOI":"10.1109\/CVPR.2019.00453"},{"key":"9376_CR45","doi-asserted-by":"crossref","unstructured":"Karras T, Laine S, Aittala M, et\u00a0al (2020) Analyzing and improving the image quality of stylegan. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 8110\u20138119","DOI":"10.1109\/CVPR42600.2020.00813"},{"key":"9376_CR46","doi-asserted-by":"crossref","unstructured":"Kemelmacher-Shlizerman I, Suwajanakorn S, Seitz SM (2014) Illumination-aware age progression. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 3334\u20133341","DOI":"10.1109\/CVPR.2014.426"},{"key":"9376_CR47","doi-asserted-by":"crossref","unstructured":"Kemmer B, Sim\u00f5es R, Lima C (2022) Face aging using generative adversarial networks. In: Generative adversarial learning: architectures and applications. Springer, pp 145\u2013168","DOI":"10.1007\/978-3-030-91390-8_7"},{"issue":"4","key":"9376_CR48","doi-asserted-by":"publisher","first-page":"1465","DOI":"10.1007\/s11760-022-02355-4","volume":"17","author":"M Khajavi","year":"2023","unstructured":"Khajavi M, Ahmadyfard A (2023) Human face aging based on active appearance model using proper feature set. Signal Image Video Process 17(4):1465\u20131473","journal-title":"Signal Image Video Process"},{"issue":"116","key":"9376_CR49","first-page":"792","volume":"198","author":"YH Kim","year":"2022","unstructured":"Kim YH, Nam SH, Hong SB et al (2022) GRA-GAN: generative adversarial network for image style transfer of gender, race, and age. Expert Syst Appl 198(116):792","journal-title":"Expert Syst Appl"},{"key":"9376_CR50","unstructured":"Kingma D, Welling M (2013) Auto-encoding variational bayes. ICLR"},{"key":"9376_CR51","doi-asserted-by":"crossref","unstructured":"Klare B, Jain AK (2010) On a taxonomy of facial features. In: 2010 4th IEEE international conference on biometrics: theory, applications and systems (BTAS). IEEE, pp 1\u20138","DOI":"10.1109\/BTAS.2010.5634533"},{"issue":"5","key":"9376_CR52","doi-asserted-by":"publisher","first-page":"96","DOI":"10.3390\/jimaging9050096","volume":"9","author":"C Korgialas","year":"2023","unstructured":"Korgialas C, Pantraki E, Bolari A et al (2023) Face aging by explainable conditional adversarial autoencoders. J Imaging 9(5):96","journal-title":"J Imaging"},{"issue":"6","key":"9376_CR53","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1145\/3065386","volume":"60","author":"A Krizhevsky","year":"2017","unstructured":"Krizhevsky A, Sutskever I, Hinton GE (2017) Imagenet classification with deep convolutional neural networks. Commun ACM 60(6):84\u201390","journal-title":"Commun ACM"},{"key":"9376_CR54","unstructured":"Kuo TH, Jia Z, Kuo TW, et\u00a0al (2023) Bitrackgan: Cascaded cyclegans to constraint face aging. arXiv:2304.11313"},{"key":"9376_CR55","doi-asserted-by":"crossref","unstructured":"Kwak Jg, Han DK, Ko H (2020) CAFE-GAN: arbitrary face attribute editing with complementary attention feature. In: Computer Vision\u2014ECCV 2020: 16th European conference, Glasgow, UK, August 23\u201328, 2020, Proceedings, Part XIV 16. Springer, pp 524\u2013540","DOI":"10.1007\/978-3-030-58568-6_31"},{"issue":"4","key":"9376_CR56","doi-asserted-by":"publisher","first-page":"442","DOI":"10.1109\/34.993553","volume":"24","author":"A Lanitis","year":"2002","unstructured":"Lanitis A, Taylor CJ, Cootes TF (2002) Toward automatic simulation of aging effects on face images. IEEE Trans Pattern Anal Mach Intell 24(4):442\u2013455","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"9376_CR57","doi-asserted-by":"crossref","unstructured":"Ledig C, Theis L, Husz\u00e1r F, et\u00a0al (2017) 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","DOI":"10.1109\/CVPR.2017.19"},{"key":"9376_CR58","unstructured":"Lee J, Yun J, Park S, et\u00a0al (2021) Improving face recognition with large age gaps by learning to distinguish children. arXiv:2110.11630"},{"key":"9376_CR59","doi-asserted-by":"crossref","unstructured":"Li Z, Jiang R, Aarabi P (2021) Continuous face aging via self-estimated residual age embedding. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 15,008\u201315,017","DOI":"10.1109\/CVPR46437.2021.01476"},{"issue":"116","key":"9376_CR60","first-page":"127","volume":"93","author":"L Liu","year":"2021","unstructured":"Liu L, Yu H, Wang S et al (2021) Learning shape and texture progression for young child face aging. Signal Process Image Commun 93(116):127","journal-title":"Signal Process Image Commun"},{"key":"9376_CR61","doi-asserted-by":"crossref","unstructured":"Liu S, Sun Y, Zhu D, et\u00a0al (2017) Face aging with contextual generative adversarial nets. In: Proceedings of the 25th ACM international conference on Multimedia, pp 82\u201390","DOI":"10.1145\/3123266.3123431"},{"issue":"2","key":"9376_CR62","doi-asserted-by":"publisher","first-page":"023,003","DOI":"10.1117\/1.JEI.30.2.023003","volume":"30","author":"W Ma","year":"2021","unstructured":"Ma W, Zhou Y, He J (2021) Semi-supervised face aging and rejuvenating. J Electron Imaging 30(2):023,003-023,003","journal-title":"J Electron Imaging"},{"key":"9376_CR63","doi-asserted-by":"crossref","unstructured":"Maeng J, Oh K, Suk HI (2023) Age-aware guidance via masking-based attention in face aging. In: 15th ACM international conference on Information and knowledge management","DOI":"10.1145\/3583780.3615183"},{"key":"9376_CR64","doi-asserted-by":"crossref","unstructured":"Makhmudkhujaev F, Hong S, Park IK (2021) Re-aging gan: toward personalized face age transformation. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp 3908\u20133917","DOI":"10.1109\/ICCV48922.2021.00388"},{"key":"9376_CR65","doi-asserted-by":"crossref","unstructured":"Mao X, Li Q, Xie H, et\u00a0al (2017) Least squares generative adversarial networks. In: Proceedings of the IEEE international conference on computer vision, pp 2794\u20132802","DOI":"10.1109\/ICCV.2017.304"},{"key":"9376_CR66","doi-asserted-by":"publisher","first-page":"6309","DOI":"10.1007\/s11042-018-6311-z","volume":"78","author":"V Martin","year":"2019","unstructured":"Martin V, Seguier R, Porcheron A et al (2019) Face aging simulation with a new wrinkle oriented active appearance model. Multimedia Tools Appl 78:6309\u20136327","journal-title":"Multimedia Tools Appl"},{"key":"9376_CR67","unstructured":"Megvii Incorporated (2012) Face++ research toolkit. http:\/\/www.faceplusplus.com"},{"key":"9376_CR68","first-page":"78","volume":"2","author":"B Mendelson","year":"2013","unstructured":"Mendelson B, Wong CH (2013) Anatomy of the aging face. Plastic Surg 2:78\u201392","journal-title":"Plastic Surg"},{"key":"9376_CR69","unstructured":"Mirza M, Osindero S (2014) Conditional generative adversarial nets. arXiv:1411.1784"},{"key":"9376_CR70","doi-asserted-by":"crossref","unstructured":"Mishra A, Krishna\u00a0Reddy S, Mittal A, et\u00a0al (2018) A generative model for zero shot learning using conditional variational autoencoders. In: Proceedings of the IEEE conference on computer vision and pattern recognition workshops, pp 2188\u20132196","DOI":"10.1109\/CVPRW.2018.00294"},{"key":"9376_CR71","doi-asserted-by":"crossref","unstructured":"Moschoglou S, Papaioannou A, Sagonas C, et\u00a0al (2017) Agedb: the first manually collected, in-the-wild age database. In: proceedings of the IEEE conference on computer vision and pattern recognition workshops, pp 51\u201359","DOI":"10.1109\/CVPRW.2017.250"},{"key":"9376_CR72","unstructured":"Nagisetty V, Graves L, Scott J, et\u00a0al (2020) xai-gan: Enhancing generative adversarial networks via explainable ai systems. arXiv:2002.10438"},{"key":"9376_CR73","unstructured":"Nickabadi A, Fard MS, Farid NM, et\u00a0al (2022) A comprehensive survey on semantic facial attribute editing using generative adversarial networks. arXiv:2205.10587"},{"key":"9376_CR74","doi-asserted-by":"crossref","unstructured":"Or-El R, Sengupta S, Fried O, et\u00a0al (2020) Lifespan age transformation synthesis. In: Computer Vision\u2013ECCV 2020: 16th European conference, Glasgow, UK, August 23\u201328, 2020, Proceedings, Part VI 16. Springer, pp 739\u2013755","DOI":"10.1007\/978-3-030-58539-6_44"},{"issue":"102","key":"9376_CR75","first-page":"961","volume":"196","author":"A Othmani","year":"2020","unstructured":"Othmani A, Taleb AR, Abdelkawy H et al (2020) Age estimation from faces using deep learning: a comparative analysis. Comput Vis Image Understand 196(102):961","journal-title":"Comput Vis Image Understand"},{"issue":"5","key":"9376_CR76","doi-asserted-by":"publisher","first-page":"947","DOI":"10.1109\/TPAMI.2010.14","volume":"32","author":"U Park","year":"2010","unstructured":"Park U, Tong Y, Jain AK (2010) Age-invariant face recognition. IEEE Trans Pattern Anal Mach Intell 32(5):947\u2013954","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"9376_CR77","doi-asserted-by":"publisher","first-page":"28,693","DOI":"10.1109\/ACCESS.2022.3157617","volume":"10","author":"H Pranoto","year":"2022","unstructured":"Pranoto H, Heryadi Y, Warnars HLHS et al (2022) Recent generative adversarial approach in face aging and dataset review. IEEE Access 10:28,693-28,716","journal-title":"IEEE Access"},{"key":"9376_CR78","doi-asserted-by":"crossref","unstructured":"Ramanathan N, Chellappa R (2006) Modeling age progression in young faces. In: 2006 IEEE computer society conference on computer vision and pattern recognition (CVPR\u201906). IEEE, pp 387\u2013394","DOI":"10.1109\/CVPR.2006.187"},{"issue":"2","key":"9376_CR79","doi-asserted-by":"publisher","first-page":"110","DOI":"10.1093\/ageing\/afj031","volume":"35","author":"H Rexbye","year":"2006","unstructured":"Rexbye H, Petersen I, Johansens M et al (2006) Influence of environmental factors on facial ageing. Age Ageing 35(2):110\u2013115","journal-title":"Age Ageing"},{"key":"9376_CR80","doi-asserted-by":"crossref","unstructured":"Ricanek K, Tesafaye T (2006) Morph: a longitudinal image database of normal adult age-progression. In: 7th international conference on automatic face and gesture recognition (FGR06). IEEE, pp 341\u2013345","DOI":"10.1109\/FGR.2006.78"},{"key":"9376_CR81","doi-asserted-by":"crossref","unstructured":"Riccio D, Tortora G, De\u00a0Marsico M, et\u00a0al (2012) Ega-ethnicity, gender and age, a pre-annotated face database. In: 2012 IEEE workshop on biometric measurements and systems for security and medical applications (BIOMS) proceedings. IEEE, pp 1\u20138","DOI":"10.1109\/BIOMS.2012.6345776"},{"key":"9376_CR82","doi-asserted-by":"crossref","unstructured":"Rombach R, Blattmann A, Lorenz D, et\u00a0al (2022) High-resolution image synthesis with latent diffusion models. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 10,684\u201310,695","DOI":"10.1109\/CVPR52688.2022.01042"},{"key":"9376_CR83","doi-asserted-by":"crossref","unstructured":"Roomi SMM, Virasundarii S, Selvamegala S, et\u00a0al (2011) Race classification based on facial features. In: 2011 3rd national conference on computer vision, pattern recognition, image processing and graphics. IEEE, pp 54\u201357","DOI":"10.1109\/NCVPRIPG.2011.19"},{"key":"9376_CR84","doi-asserted-by":"publisher","DOI":"10.1007\/s12652-022-03897-8","author":"M Rostami","year":"2022","unstructured":"Rostami M, Farajollahi A, Parvin H (2022) Deep learning-based face detection and recognition on drones. J Ambient Intell Humaniz Comput. https:\/\/doi.org\/10.1007\/s12652-022-03897-8","journal-title":"J Ambient Intell Humaniz Comput"},{"key":"9376_CR85","unstructured":"Salimans T, Goodfellow I, Zaremba W, et\u00a0al (2016) Improved techniques for training gans. In: Advances in neural information processing systems, vol 29"},{"key":"9376_CR86","doi-asserted-by":"publisher","first-page":"249","DOI":"10.1016\/j.neucom.2016.01.101","volume":"208","author":"X Shu","year":"2016","unstructured":"Shu X, Xie GS, Li Z et al (2016) Age progression: current technologies and applications. Neurocomputing 208:249\u2013261","journal-title":"Neurocomputing"},{"key":"9376_CR87","unstructured":"Simonite T (2006) Virtual face-ageing may help find missing persons. NewScientist com. http:\/\/technologynewscientist-com\/channel\/tech\/forensic-science"},{"key":"9376_CR88","unstructured":"Simonyan K, Zisserman A (2014) Very deep convolutional networks for large-scale image recognition. arXiv:1409.1556"},{"key":"9376_CR89","unstructured":"Sohl-Dickstein J, Weiss E, Maheswaranathan N, et\u00a0al (2015) Deep unsupervised learning using nonequilibrium thermodynamics. In: International conference on machine learning, PMLR, pp 2256\u20132265"},{"key":"9376_CR90","doi-asserted-by":"crossref","unstructured":"Song J, Zhang J, Gao L, et\u00a0al (2018) Dual conditional gans for face aging and rejuvenation. In: IJCAI, pp 899\u2013905","DOI":"10.24963\/ijcai.2018\/125"},{"key":"9376_CR91","doi-asserted-by":"publisher","first-page":"791","DOI":"10.1109\/TMM.2021.3059336","volume":"24","author":"J Song","year":"2021","unstructured":"Song J, Zhang J, Gao L et al (2021) AgeGAN++: Face aging and rejuvenation with dual conditional GANs. IEEE Trans Multimedia 24:791\u2013804","journal-title":"IEEE Trans Multimedia"},{"key":"9376_CR92","unstructured":"Song Y, Sohl-Dickstein J, Kingma DP, et\u00a0al (2020) Score-based generative modeling through stochastic differential equations. arXiv:2011.13456"},{"key":"9376_CR93","doi-asserted-by":"crossref","unstructured":"Sun Y, Wang X, Tang X (2013) Deep convolutional network cascade for facial point detection. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 3476\u20133483","DOI":"10.1109\/CVPR.2013.446"},{"issue":"3","key":"9376_CR94","first-page":"385","volume":"32","author":"J Suo","year":"2009","unstructured":"Suo J, Zhu SC, Shan S et al (2009) A compositional and dynamic model for face aging. IEEE Trans Pattern Anal Mach Intell 32(3):385\u2013401","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"4","key":"9376_CR95","first-page":"113","volume":"13","author":"K Sveikata","year":"2011","unstructured":"Sveikata K, Balciuniene I, Tutkuviene J et al (2011) Factors influencing face aging: literature review. Stomatologija 13(4):113\u2013116","journal-title":"Stomatologija"},{"key":"9376_CR96","doi-asserted-by":"crossref","unstructured":"Wang W, Cui Z, Yan Y, et\u00a0al (2016) Recurrent face aging. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 2378\u20132386","DOI":"10.1109\/CVPR.2016.261"},{"key":"9376_CR97","doi-asserted-by":"crossref","unstructured":"Wang Z, Tang X, Luo W, et\u00a0al (2018) Face aging with identity-preserved conditional generative adversarial networks. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 7939\u20137947","DOI":"10.1109\/CVPR.2018.00828"},{"key":"9376_CR98","unstructured":"Xiao T, Xu Y, Yang K, et\u00a0al (2015) The application of two-level attention models in deep convolutional neural network for fine-grained image classification. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 842\u2013850"},{"key":"9376_CR99","unstructured":"Xu K, Ba J, Kiros R, et\u00a0al (2015) Show, attend and tell: neural image caption generation with visual attention. In: International conference on machine learning, PMLR, pp 2048\u20132057"},{"issue":"103","key":"9376_CR100","first-page":"945","volume":"100","author":"C Yang","year":"2020","unstructured":"Yang C, Lv Z (2020) Gender based face aging with cycle-consistent adversarial networks. Image Vis Comput 100(103):945","journal-title":"Image Vis Comput"},{"key":"9376_CR101","doi-asserted-by":"crossref","unstructured":"Yang H, Huang D, Wang Y, et\u00a0al (2018a) Learning face age progression: a pyramid architecture of gans. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 31\u201339","DOI":"10.1109\/CVPR.2018.00011"},{"key":"9376_CR102","doi-asserted-by":"crossref","unstructured":"Yang TY, Huang YH, Lin YY, et\u00a0al (2018b) Ssr-net: A compact soft stagewise regression network for age estimation. In: IJCAI, p\u00a07","DOI":"10.24963\/ijcai.2018\/150"},{"key":"9376_CR103","doi-asserted-by":"crossref","unstructured":"Yao X, Puy G, Newson A, et\u00a0al (2021) High resolution face age editing. In: 2020 25th international conference on pattern recognition (ICPR). IEEE, pp 8624\u20138631","DOI":"10.1109\/ICPR48806.2021.9412383"},{"issue":"7546","key":"9376_CR104","doi-asserted-by":"publisher","first-page":"164","DOI":"10.1038\/nature14380","volume":"520","author":"J Yin","year":"2015","unstructured":"Yin J, Boyce MC (2015) Unique wrinkles as identity tags. Nature 520(7546):164\u2013165","journal-title":"Nature"},{"key":"9376_CR105","unstructured":"Zhang H, Goodfellow I, Metaxas D, et\u00a0al (2019) Self-attention generative adversarial networks. In: International conference on machine learning, PMLR, pp 7354\u20137363"},{"key":"9376_CR106","doi-asserted-by":"crossref","unstructured":"Zhang R, Isola P, Efros AA, et\u00a0al (2018) The unreasonable effectiveness of deep features as a perceptual metric. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 586\u2013595","DOI":"10.1109\/CVPR.2018.00068"},{"key":"9376_CR107","doi-asserted-by":"crossref","unstructured":"Zhang Y, Liu L, Li C, et\u00a0al (2017a) Quantifying facial age by posterior of age comparisons. arXiv:1708.09687","DOI":"10.5244\/C.31.108"},{"key":"9376_CR108","doi-asserted-by":"crossref","unstructured":"Zhang Z, Song Y, Qi H (2017b) Age progression\/regression by conditional adversarial autoencoder. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 5810\u20135818","DOI":"10.1109\/CVPR.2017.463"},{"key":"9376_CR109","doi-asserted-by":"crossref","unstructured":"Zhao J, Cheng Y, Cheng Y, et\u00a0al (2019) Look across elapse: Disentangled representation learning and photorealistic cross-age face synthesis for age-invariant face recognition. In: Proceedings of the AAAI conference on artificial intelligence, pp 9251\u20139258","DOI":"10.1609\/aaai.v33i01.33019251"},{"key":"9376_CR110","doi-asserted-by":"crossref","unstructured":"Zhu H, Huang Z, Shan H et al (2020) Look globally, age locally: Face aging with an attention mechanism. In: ICASSP 2020-2020 IEEE international conference on acoustics, speech and signal processing (ICASSP). IEEE, pp 1963\u20131967","DOI":"10.1109\/ICASSP40776.2020.9054553"},{"key":"9376_CR111","doi-asserted-by":"crossref","unstructured":"Zhu JY, Park T, Isola P, et\u00a0al (2017) Unpaired image-to-image translation using cycle-consistent adversarial networks. In: Proceedings of the IEEE international conference on computer vision, pp 2223\u20132232","DOI":"10.1109\/ICCV.2017.244"},{"key":"9376_CR112","doi-asserted-by":"crossref","unstructured":"Zoran D, Chrzanowski M, Huang PS, et\u00a0al (2020) Towards robust image classification using sequential attention models. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 9483\u20139492","DOI":"10.1109\/CVPR42600.2020.00950"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-023-09376-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-023-09376-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-023-09376-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,8]],"date-time":"2024-11-08T18:18:40Z","timestamp":1731089920000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-023-09376-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1,20]]},"references-count":112,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2024,3]]}},"alternative-id":["9376"],"URL":"https:\/\/doi.org\/10.1007\/s00521-023-09376-1","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,1,20]]},"assertion":[{"value":"27 April 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 December 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 January 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}