{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T15:45:57Z","timestamp":1778082357540,"version":"3.51.4"},"reference-count":40,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61836011"],"award-info":[{"award-number":["61836011"]}],"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":["61473271"],"award-info":[{"award-number":["61473271"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"crossref","award":["WK2090090023"],"award-info":[{"award-number":["WK2090090023"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"crossref"}]},{"name":"GPU Computing Cluster of the Data Center, School of Information Science and Technology, University of Science and Technology of China"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2019]]},"DOI":"10.1109\/access.2019.2941272","type":"journal-article","created":{"date-parts":[[2019,9,13]],"date-time":"2019-09-13T20:26:02Z","timestamp":1568406362000},"page":"132594-132608","source":"Crossref","is-referenced-by-count":17,"title":["ResAttr-GAN: Unpaired Deep Residual Attributes Learning for Multi-Domain Face Image Translation"],"prefix":"10.1109","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9023-0066","authenticated-orcid":false,"given":"Rentuo","family":"Tao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ziqiang","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Renshuai","family":"Tao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2332-3959","authenticated-orcid":false,"given":"Bin","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2003.819861"},{"key":"ref38","first-page":"2234","article-title":"Improved techniques for training GANs","author":"salimans","year":"2016","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref33","first-page":"9859","article-title":"Semantic component decomposition for face attribute manipulation","author":"chen","year":"2019","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit"},{"key":"ref32","article-title":"Instance-level facial attributes transfer with geometry-aware flow","author":"yin","year":"2018","journal-title":"arXiv 1811 12670"},{"key":"ref31","article-title":"The GAN that warped: Semantic attribute editing with unpaired data","author":"dorta","year":"2018","journal-title":"arXiv 1811 12784"},{"key":"ref30","first-page":"3673","article-title":"STGAN: A unified selective transfer network for arbitrary image attribute editing","author":"liu","year":"2019","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit"},{"key":"ref37","first-page":"6626","article-title":"GANs trained by a two time-scale update rule converge to a local nash equilibrium","author":"heusel","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref36","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2014","journal-title":"arXiv 1412 6980"},{"key":"ref35","first-page":"234","article-title":"U-Net: Convolutional networks for biomedical image segmentation","author":"ronneberger","year":"2015","journal-title":"Proc Int Conf Med Image Comput Comput -Assist Intervent"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.425"},{"key":"ref10","first-page":"5769","article-title":"Improved training of wasserstein GANs","author":"gulrajani","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.632"},{"key":"ref12","first-page":"700","article-title":"Unsupervised image-to-image translation networks","author":"liu","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref13","article-title":"Auto-encoding variational Bayes","author":"kingma","year":"2013","journal-title":"arXiv 1312 6114"},{"key":"ref14","first-page":"469","article-title":"Coupled generative adversarial networks","author":"liu","year":"2016","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref15","first-page":"1857","article-title":"Learning to discover cross-domain relations with generative adversarial networks","volume":"70","author":"kim","year":"2017","journal-title":"Proc 34th Int Conf Mach Learn"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01246-5_3"},{"key":"ref17","first-page":"2408","article-title":"Homomorphic latent space interpolation for unpaired image-to-image translation","author":"chen","year":"2019","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit"},{"key":"ref18","first-page":"10042","article-title":"Beautyglow: On-demand makeup transfer framework with reversible generative network","author":"chen","year":"2019","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit"},{"key":"ref19","article-title":"Autoencoding beyond pixels using a learned similarity metric","author":"larsen","year":"2015","journal-title":"arXiv 1512 09300"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46493-0_47"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01231-1_26"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01249-6_11"},{"key":"ref3","article-title":"Deep identity-aware transfer of facial attributes","author":"li","year":"2016","journal-title":"arXiv 1610 05586"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2019.2916751"},{"key":"ref29","first-page":"7992","article-title":"Conditional adversarial generative flow for controllable image synthesis","author":"liu","year":"2019","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.135"},{"key":"ref8","first-page":"1","article-title":"Siamese neural networks for one-shot image recognition","volume":"2","author":"koch","year":"2015","journal-title":"Proc ICML Deep Learn Workshop"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.244"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01249-6_50"},{"key":"ref9","first-page":"2672","article-title":"Generative adversarial nets","author":"goodfellow","year":"2014","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00916"},{"key":"ref20","article-title":"Mask-aware photorealistic face attribute manipulation","author":"sun","year":"2018","journal-title":"arXiv 1804 08882"},{"key":"ref22","first-page":"5967","article-title":"Fader networks: Manipulating images by sliding attributes","author":"lample","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.645"},{"key":"ref24","article-title":"Invertible conditional GANs for image editing","author":"perarnau","year":"2016","journal-title":"arXiv 1611 06355"},{"key":"ref23","article-title":"Adversarial information factorization","author":"creswell","year":"2017","journal-title":"arXiv 1711 05175"},{"key":"ref26","article-title":"GeneGAN: Learning object transfiguration and attribute subspace from unpaired data","author":"zhou","year":"2017","journal-title":"arXiv 1705 04932"},{"key":"ref25","article-title":"DNA-GAN: Learning disentangled representations from multi-attribute images","author":"xiao","year":"2017","journal-title":"arXiv 1711 05415"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8600701\/08836502.pdf?arnumber=8836502","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,8,10]],"date-time":"2021-08-10T19:41:09Z","timestamp":1628624469000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8836502\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"references-count":40,"URL":"https:\/\/doi.org\/10.1109\/access.2019.2941272","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]}}}