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Porter, \u201cMisleading first impressions,\u201d Psychological Science, vol.25, no.7, pp.1404-1417, 2014. 10.1177\/0956797614532474","DOI":"10.1177\/0956797614532474"},{"key":"2","doi-asserted-by":"publisher","unstructured":"[2] R. Jenkins, D. White, X. Van Montfort, and A.M. Burton, \u201cVariability in photos of the same face,\u201d Cognition, vol.121, no.3, pp.313-323, 2011. 10.1016\/j.cognition.2011.08.001","DOI":"10.1016\/j.cognition.2011.08.001"},{"key":"3","doi-asserted-by":"publisher","unstructured":"[3] J.C. Silveira Jacques Junior, Y. G\u00fc\u00e7l\u00fct\u00fcrk, M. Perez, U. G\u00fc\u00e7l\u00fc, C. Andujar, X. Bar\u00f3, H.J. Escalante, I. Guyon, M.A.J. Van Gerven, R. Van Lier, and S. Escalera, \u201cFirst impressions: a survey on vision-based apparent personality trait analysis,\u201d IEEE Transactions on Affective Computing, p.1, 2019. 10.1109\/taffc.2019.2930058","DOI":"10.1109\/TAFFC.2019.2930058"},{"key":"4","doi-asserted-by":"publisher","unstructured":"[4] R.J.W. Vernon, C.A.M. Sutherland, A.W. Young, and T. Hartley, \u201cModeling first impressions from highly variable facial images,\u201d Proc. National Academy of Sciences, vol.111, no.32, pp.E3353-E3361, 2014. 10.1073\/pnas.1409860111","DOI":"10.1073\/pnas.1409860111"},{"key":"5","doi-asserted-by":"crossref","unstructured":"[5] A. Khosla, W.A. Bainbridge, A. Torralba, and A. Oliva, \u201cModifying the memorability of face photographs,\u201d Proc. IEEE International Conference on Computer Vision, pp.3200-3207, 2013. 10.1109\/iccv.2013.397","DOI":"10.1109\/ICCV.2013.397"},{"key":"6","doi-asserted-by":"crossref","unstructured":"[6] T. Alashkar, S. Jiang, S. Wang, and Y. Fu, \u201cExamples-rules guided deep neural network for makeup recommendation,\u201d Proc. AAAI Conference on Artificial Intelligence, pp.941-947, 2017.","DOI":"10.1609\/aaai.v31i1.10626"},{"key":"7","doi-asserted-by":"publisher","unstructured":"[7] L. Liu, J. Xing, S. Liu, H. Xu, X. Zhou, and S. Yan, \u201c\u201cWow! you are so beautiful today!\u201d,\u201d ACM Transactions on Multimedia Computing, Communications, and Applications, vol.11, no.1s, pp.1-22, 2014. 10.1145\/2659234","DOI":"10.1145\/2659234"},{"key":"8","doi-asserted-by":"publisher","unstructured":"[8] Y. Koyama, I. Sato, D. Sakamoto, and T. Igarashi, \u201cSequential line search for efficient visual design optimization by crowds,\u201d ACM Transactions on Graphics, vol.36, no.4, 2017. 10.1145\/3072959.3073598","DOI":"10.1145\/3072959.3073598"},{"key":"9","doi-asserted-by":"publisher","unstructured":"[9] F. Chen, X. Xiao, and D. Zhang, \u201cData-driven facial beauty analysis: prediction, retrieval and manipulation,\u201d IEEE Transactions on Affective Computing, vol.9, no.2, pp.205-216, 2018. 10.1109\/taffc.2016.2599534","DOI":"10.1109\/TAFFC.2016.2599534"},{"key":"10","unstructured":"[10] M. Sun, D. Zhang, and J. Yang, \u201cFace attractiveness improvement using beauty prototypes and decision,\u201d Proc. Asian Conference on Pattern Recognition, pp.283-287, 2011. 10.1109\/acpr.2011.6166544"},{"key":"11","doi-asserted-by":"publisher","unstructured":"[11] S. Melacci, L. Sarti, M. Maggini, and M. Gori, \u201cA template-based approach to automatic face enhancement,\u201d Pattern Analysis and Applications, vol.13, no.3, pp.289-300, 2010. 10.1007\/s10044-009-0155-0","DOI":"10.1007\/s10044-009-0155-0"},{"key":"12","doi-asserted-by":"publisher","unstructured":"[12] T. Leyvand, D. Cohen-Or, G. Dror, and D. Lischinski, \u201cData-driven enhancement of facial attractiveness,\u201d ACM Transactions on Graphics, vol.27, no.3, p.1, 2008. 10.1145\/1360612.1360637","DOI":"10.1145\/1360612.1360637"},{"key":"13","doi-asserted-by":"crossref","unstructured":"[13] R.M. Stolier, E. Hehman, M.D. Keller, M. Walker, and J.B.Freeman, \u201cThe conceptual structure of face impressions,\u201d Proc. National Academy of Sciences, vol.115, no.37, pp.9210-9215, 2018.","DOI":"10.1073\/pnas.1807222115"},{"key":"14","doi-asserted-by":"crossref","unstructured":"[14] M. Miyata and K. Aizawa, \u201cImpression estimation for deformed portraits with a landmark-based ranking network,\u201d Proc. IEEE International Conference on Image Processing, pp.1950-1954, 2019. 10.1109\/icip.2019.8803157","DOI":"10.1109\/ICIP.2019.8803157"},{"key":"15","doi-asserted-by":"crossref","unstructured":"[15] S. Suwajanakorn, S.M. Seitz, and I. Kemelmacher-Shlizerman, \u201cWhat makes Tom Hanks look like Tom Hanks,\u201d Proc. IEEE International Conference on Computer Vision, pp.3952-3960, 2015. 10.1109\/iccv.2015.450","DOI":"10.1109\/ICCV.2015.450"},{"key":"16","doi-asserted-by":"publisher","unstructured":"[16] B. Fink, K. Grammer, and R. Thornhill, \u201cHuman (Homo sapiens) facial attractiveness in relation to skin texture and color,\u201d Journal of Comparative Psychology, vol.115, no.1, pp.92-99, 2001. 10.1037\/0735-7036.115.1.92","DOI":"10.1037\/0735-7036.115.1.92"},{"key":"17","doi-asserted-by":"crossref","unstructured":"[17] H. Doughty, D. Damen, and W. Mayol-Cuevas, \u201cWho&apos;s better? who&apos;s best? pairwise deep ranking for skill determination,\u201d Proc. Conference on Computer Vision and Pattern Recognition, pp.6057-6066, 2018. 10.1109\/cvpr.2018.00634","DOI":"10.1109\/CVPR.2018.00634"},{"key":"18","doi-asserted-by":"crossref","unstructured":"[18] C. Cao, I.S. Kwak, S. Belongie, D. Kriegman, and H. Ai, \u201cAdaptive ranking of facial attractiveness,\u201d Proc. IEEE International Conference on Multimedia and Expo, pp.1-6, July 2014. 10.1109\/icme.2014.6890147","DOI":"10.1109\/ICME.2014.6890147"},{"key":"19","doi-asserted-by":"crossref","unstructured":"[19] H. Altwaijry and S. Belongie, \u201cRelative ranking of facial attractiveness,\u201d Proc. IEEE Workshop on Applications of Computer Vision, pp.117-124, 2013. 10.1109\/wacv.2013.6475008","DOI":"10.1109\/WACV.2013.6475008"},{"key":"20","doi-asserted-by":"crossref","unstructured":"[20] J. Ren, X. Shen, and Z. Lin, \u201cPersonalized image aesthetics,\u201d Proc. IEEE International Conference on Computer Vision, pp.638-647, 2017.","DOI":"10.1109\/ICCV.2017.76"},{"key":"21","doi-asserted-by":"crossref","unstructured":"[21] A. Deza, S. Barbara, D. Parikh, and V. Tech, \u201cUnderstanding Image Virality,\u201d Proc. IEEE International Conference on Computer Vision and Pattern Recognition, pp.1818-1826, 2015.","DOI":"10.1109\/CVPR.2015.7298791"},{"key":"22","doi-asserted-by":"crossref","unstructured":"[22] Z. Meng, N. Adluru, H.J. Kim, G. Fung, and V. Singh, \u201cEfficient relative attribute learning using graph neural networks,\u201d Proc. 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Joachims, \u201cOptimizing search engines using clickthrough data,\u201d Proc. International Conference on Knowledge Discovery and Data mining, pp.133-142, 2002. 10.1145\/775047.775067","DOI":"10.1145\/775047.775067"},{"key":"27","doi-asserted-by":"crossref","unstructured":"[27] A. Yu and K. Grauman, \u201cFine-grained visual comparisons with local learning,\u201d Proc. Conference on Computer Vision and Pattern Recognition, pp.192-199, 2014. 10.1109\/cvpr.2014.32","DOI":"10.1109\/CVPR.2014.32"},{"key":"28","doi-asserted-by":"crossref","unstructured":"[28] A. Yu and K. Grauman, \u201cThinking outside the pool: active training image creation for relative attributes,\u201d Proc. IEEE International Conference on Computer Vision and Pattern Recognition, pp.708-718, 2019. 10.1109\/cvpr.2019.00080","DOI":"10.1109\/CVPR.2019.00080"},{"key":"29","doi-asserted-by":"crossref","unstructured":"[29] A. Yu and K. Grauman, \u201cSemantic jitter: dense supervision for visual comparisons via synthetic images,\u201d Proc. IEEE International Conference on Computer Vision, vol.1, pp.5571-5580, 2017. 10.1109\/iccv.2017.594","DOI":"10.1109\/ICCV.2017.594"},{"key":"30","doi-asserted-by":"crossref","unstructured":"[30] C. Burges, T. Shaked, E. Renshaw, A. Lazier, M. Deeds, N.Hamilton, and G. Hullender, \u201cLearning to rank using gradient descent,\u201d Proc. International Conference on Machine learning, pp.89-96, 2005. 10.1145\/1102351.1102363","DOI":"10.1145\/1102351.1102363"},{"key":"31","doi-asserted-by":"crossref","unstructured":"[31] X. Zheng, Y. Guo, H. Huang, Y. Li, and R. He, \u201cA survey of deep facial attribute analysis,\u201d International Journal of Computer Vision, vol.128, pp.2002-2034, 2020.","DOI":"10.1007\/s11263-020-01308-z"},{"key":"32","unstructured":"[32] S. Liu, X. Ou, R. Qian, W. Wang, and X. Cao, \u201cMakeup like a superstar: deep localized makeup transfer network,\u201d Proc. International Joint Conference on Artificial Intelligence, pp.2568-2575, 2016."},{"key":"33","unstructured":"[33] D. Guo and T. Sim, \u201cDigital face makeup by example,\u201d Proc. IEEE International Conference on Computer Vision and Pattern Recognition, pp.73-79, 2009. 10.1109\/cvprw.2009.5206833"},{"key":"34","unstructured":"[34] R. Yeh, Z. Liu, D.B. Goldman, and A. Agarwala, \u201cSemantic facial expression editing using autoencoded flow,\u201d arXiv preprint arXiv:1611.09961, 2016."},{"key":"35","doi-asserted-by":"crossref","unstructured":"[35] Z. Shu, \u201cEyeopener: editing eyes in the wild,\u201d ACM Transactions on Graphics, vol.36, no.1, 2016.","DOI":"10.1145\/2926713"},{"key":"36","doi-asserted-by":"publisher","unstructured":"[36] F. Yang, D. Metaxas, J. Wang, E. Shechtman, and L. Bourdev, \u201cExpression flow for 3d-aware face component transfer,\u201d ACM Transactions on Graphics, vol.30, no.4, pp.1-10, 2011. 10.1145\/2010324.1964955","DOI":"10.1145\/2010324.1964955"},{"key":"37","doi-asserted-by":"crossref","unstructured":"[37] M. Liu, Y. Ding, M. Xia, X. Liu, E. Ding, W. Zuo, and S. Wen, \u201cSTGAN: a unified selective transfer network for arbitrary image attribute editing,\u201d Proc. IEEE International Conference on Computer Vision and Pattern Recognition, pp.3668-3677, 2019. 10.1109\/cvpr.2019.00379","DOI":"10.1109\/CVPR.2019.00379"},{"key":"38","unstructured":"[38] G.B. Huang, M. Ramesh, T. Berg, and E. Learned-Miller, \u201cLabeled faces in the wild: a database for studying face recognition in unconstrained environments,\u201d Tech. Rep. 07-49, University of Massachusetts, Amherst, Oct. 2007."},{"key":"39","doi-asserted-by":"publisher","unstructured":"[39] W.A. Bainbridge, P. Isola, and A. Oliva, \u201cThe intrinsic memorability of face photographs,\u201d Journal of Experimental Psychology: General, vol.142, no.4, pp.1323-1334, 2013. 10.1037\/a0033872","DOI":"10.1037\/a0033872"},{"key":"40","doi-asserted-by":"crossref","unstructured":"[40] Z. Liu, P. Luo, X. Wang, and X. Tang, \u201cDeep learning face attributes in the wild,\u201d Proc. International Conference on Computer Vision, 2015. 10.1109\/iccv.2015.425","DOI":"10.1109\/ICCV.2015.425"},{"key":"41","doi-asserted-by":"publisher","unstructured":"[41] N.L. Etcoff, S. Stock, L.E. Haley, S.A. Vickery, and D.M. House, \u201cCosmetics as a feature of the extended human phenotype: modulation of the perception of biologically important facial signals,\u201d PLoS ONE, vol.6, no.10, p.e25656, 2011. 10.1371\/journal.pone.0025656","DOI":"10.1371\/journal.pone.0025656"},{"key":"42","doi-asserted-by":"publisher","unstructured":"[42] J.-Y. Zhu, A. Agarwala, A.A. Efros, E. Shechtman, and J. Wang, \u201cMirror mirror: crowdsourcing better portraits,\u201d ACM Transactions on Graphics, vol.33, no.6, pp.1-12, 2014. 10.1145\/2661229.2661287","DOI":"10.1145\/2661229.2661287"},{"key":"43","doi-asserted-by":"crossref","unstructured":"[43] M.R. Barrick and M.K. Mount, \u201cThe big five personality dimensions and job performance: a meta-analysis,\u201d Personnel Psychology, vol.44, no.1, pp.1-26, 1991. 10.1111\/j.1744-6570.1991.tb00688.x","DOI":"10.1111\/j.1744-6570.1991.tb00688.x"},{"key":"44","doi-asserted-by":"publisher","unstructured":"[44] S. Kobayashi, \u201cThe aim and method of the color image scale,\u201d Color research and application, vol.6, no.2, pp.93-107, 1981. 10.1002\/col.5080060210","DOI":"10.1002\/col.5080060210"},{"key":"45","unstructured":"[45] J. Jia, J. Huang, G. Shen, T. He, Z. Liu, H. Luan, and C. Yan, \u201cLearning to appreciate the aesthetic effects of clothing,\u201d Proc. AAAI Conference on Artificial Intelligence, pp.1216-1222, 2016."},{"key":"46","doi-asserted-by":"publisher","unstructured":"[46] A. Jahanian, S. Keshvari, S.V.N. Vishwanathan, and J.P. Allebach,\u201cColors-messengers of concepts,\u201d ACM Transactions on Computer-Human Interaction, vol.24, no.1, pp.1-39, 2017. 10.1145\/3009924","DOI":"10.1145\/3009924"},{"key":"47","doi-asserted-by":"publisher","unstructured":"[47] S. Schaefer, T. McPhail, and J. Warren, \u201cImage deformation using moving least squares,\u201d ACM Transactions on Graphics, vol.25, no.3, pp.533-540, 2006. 10.1145\/1141911.1141920","DOI":"10.1145\/1141911.1141920"},{"key":"48","unstructured":"[48] K. Tsukida and M.R. Gupta, \u201cHow to analyze paired comparison data,\u201d tech. rep., Dept. of Electrical Engineering, University of Washington, 2011."},{"key":"49","doi-asserted-by":"crossref","unstructured":"[49] J. Hu, L. Shen, and G. Sun, \u201cSqueeze-and-excitation networks,\u201d Proc. IEEE Conference on Computer Vision and Pattern Recognition, pp.7132-7141, 2018. 10.1109\/cvpr.2018.00745","DOI":"10.1109\/CVPR.2018.00745"},{"key":"50","unstructured":"[50] I. Loshchilov and F. Hutter, \u201cSGDR: stochastic gradient descent with warm restarts,\u201d Proc. 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