{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T23:48:58Z","timestamp":1778629738431,"version":"3.51.4"},"reference-count":82,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"10","license":[{"start":{"date-parts":[[2019,10,1]],"date-time":"2019-10-01T00:00:00Z","timestamp":1569888000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,10,1]],"date-time":"2019-10-01T00:00:00Z","timestamp":1569888000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,10,1]],"date-time":"2019-10-01T00:00:00Z","timestamp":1569888000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. on Image Process."],"published-print":{"date-parts":[[2019,10]]},"DOI":"10.1109\/tip.2019.2914583","type":"journal-article","created":{"date-parts":[[2019,5,8]],"date-time":"2019-05-08T20:10:09Z","timestamp":1557346209000},"page":"4845-4856","source":"Crossref","is-referenced-by-count":37,"title":["Show, Attend, and Translate: Unsupervised Image Translation With Self-Regularization and Attention"],"prefix":"10.1109","volume":"28","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6553-7963","authenticated-orcid":false,"given":"Chao","family":"Yang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Taehwan","family":"Kim","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ruizhe","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hao","family":"Peng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9474-5035","authenticated-orcid":false,"given":"C.-C. Jay","family":"Kuo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref73","first-page":"2048","article-title":"Show, attend and tell: Neural image caption generation with visual attention","author":"xu","year":"2015","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46478-7_28"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.164"},{"key":"ref70","first-page":"318","article-title":"Generative image modeling using style and structure adversarial networks","author":"wang","year":"2016","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref76","author":"zhang","year":"2016","journal-title":"StackGAN Text to photo-realistic image synthesis with stacked generative adversarial networks"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46487-9_40"},{"key":"ref74","author":"xu","year":"2017","journal-title":"AttnGAN Fine-grained text to image generation with attentional generative adversarial networks"},{"key":"ref39","author":"ledig","year":"2016","journal-title":"Photo-realistic single image super-resolution using a generative adversarial network"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46484-8_31"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00068"},{"key":"ref79","author":"zhao","year":"2016","journal-title":"Energy-based Generative Adversarial Network"},{"key":"ref33","author":"kim","year":"2017","journal-title":"Learning to discover cross-domain relations with generative adversarial networks"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.182"},{"key":"ref31","author":"karras","year":"2017","journal-title":"Progressive growing of GANs for improved quality stability and variation"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2017.7989092"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1145\/2601097.2601101"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.399"},{"key":"ref35","author":"kingma","year":"2013","journal-title":"Auto-encoding variational bayes"},{"key":"ref34","author":"kingma","year":"2014","journal-title":"Adam A method for stochastic optimization"},{"key":"ref60","author":"rusu","year":"2016","journal-title":"Sim-to-real robot learning from pixels with progressive nets"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1145\/2508363.2508419"},{"key":"ref61","first-page":"2234","article-title":"Improved techniques for training GANs","author":"salimans","year":"2016","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.241"},{"key":"ref28","author":"isola","year":"2016","journal-title":"Image-to-image translation with conditional adversarial networks"},{"key":"ref64","author":"simonyan","year":"2014","journal-title":"Very Deep Convolutional Networks for Large-scale Image Recognition"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01219-9_11"},{"key":"ref65","first-page":"8","article-title":"Return of frustratingly easy domain adaptation","volume":"6","author":"sun","year":"2016","journal-title":"Proc AAAI"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.163"},{"key":"ref29","first-page":"694","article-title":"Perceptual losses for real-time style transfer and super-resolution","author":"johnson","year":"2016","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref67","article-title":"Towards adapting deep visuomotor representations from simulated to real environments","volume":"abs 1511 7111","author":"tzeng","year":"2015","journal-title":"CoRR"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.463"},{"key":"ref69","author":"wang","year":"2017","journal-title":"High-resolution image synthesis and semantic manipulation with conditional gans"},{"key":"ref2","author":"arjovsky","year":"2017","journal-title":"Wasserstein GAN"},{"key":"ref1","author":"ajakan","year":"2014","journal-title":"Domain-adversarial neural networks"},{"key":"ref20","first-page":"2672","article-title":"Generative adversarial nets","author":"goodfellow","year":"2014","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref22","first-page":"5767","article-title":"Improved training of Wasserstein GANs","author":"gulrajani","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref21","first-page":"723","article-title":"A kernel two-sample test","volume":"13","author":"gretton","year":"2012","journal-title":"J Mach Learn Res"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1145\/383259.383295"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.167"},{"key":"ref25","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":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.304"},{"key":"ref51","author":"miyato","year":"2018","journal-title":"Spectral normalization for generative adversarial networks"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.352"},{"key":"ref57","first-page":"102","article-title":"Playing for data: Ground truth from computer games","author":"richter","year":"2016","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref56","first-page":"1278","article-title":"Stochastic backpropagation and variational inference in deep latent Gaussian models","volume":"2","author":"rezende","year":"2014","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref55","author":"reed","year":"2016","journal-title":"Generative adversarial text to image synthesis"},{"key":"ref54","author":"radford","year":"2015","journal-title":"Unsupervised Representation learning with deep convolutional generative adversarial networks CoRR"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-49409-8_75"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2012.6248092"},{"key":"ref10","first-page":"577","article-title":"Attention-based models for speech recognition","author":"chorowski","year":"2015","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref11","author":"christiano","year":"2016","journal-title":"Transfer from simulation to real world through learning deep inverse dynamics model"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.272"},{"key":"ref12","first-page":"3","article-title":"The cityscapes dataset","volume":"1","author":"cordts","year":"2015","journal-title":"Proc CVPR Workshop Future Datasets Vision"},{"key":"ref13","first-page":"323","article-title":"Neural network recognizer for hand-written zip code digits","author":"denker","year":"1989","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10593-2_13"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.304"},{"key":"ref82","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2017.7989381"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00923"},{"key":"ref81","first-page":"465","article-title":"Toward multimodal image-to-image translation","author":"zhu","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref17","first-page":"2030","article-title":"Domain-adversarial training of neural networks","volume":"17","author":"ganin","year":"2015","journal-title":"J Mach Learn Res"},{"key":"ref18","author":"gatys","year":"2015","journal-title":"A neural algorithm of artistic style"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.265"},{"key":"ref80","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.244"},{"key":"ref4","author":"berthelot","year":"2017","journal-title":"BEGAN Boundary Equilibrium Generative Adversarial Networks"},{"key":"ref3","author":"bahdanau","year":"2014","journal-title":"Neural machine translation by jointly learning to align and translate"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/311535.311556"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/AFGR.2002.1004155"},{"key":"ref8","first-page":"343","article-title":"Domain separation networks","author":"bousmalis","year":"2016","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.18"},{"key":"ref49","author":"mao","year":"2016","journal-title":"Least squares generative adversarial networks"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7299009"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.425"},{"key":"ref48","author":"mahendran","year":"2016","journal-title":"Researchdoom and cocodoom Learning computer vision with games"},{"key":"ref47","author":"long","year":"2015","journal-title":"Learning transferable features with deep adaptation networks"},{"key":"ref42","author":"liu","year":"2017","journal-title":"Unsupervised image-to-image translation networks"},{"key":"ref41","author":"lindvall","year":"2002","journal-title":"Lectures on the Coupling Method"},{"key":"ref44","first-page":"469","article-title":"Coupled generative adversarial networks","author":"liu","year":"2016","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref43","first-page":"700","article-title":"Unsupervised image-to-image translation networks","author":"liu","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"}],"container-title":["IEEE Transactions on Image Processing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/83\/8784442\/08709985.pdf?arnumber=8709985","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,13]],"date-time":"2022-07-13T20:44:26Z","timestamp":1657745066000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8709985\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,10]]},"references-count":82,"journal-issue":{"issue":"10"},"URL":"https:\/\/doi.org\/10.1109\/tip.2019.2914583","relation":{},"ISSN":["1057-7149","1941-0042"],"issn-type":[{"value":"1057-7149","type":"print"},{"value":"1941-0042","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,10]]}}}