{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,16]],"date-time":"2026-01-16T12:03:51Z","timestamp":1768565031311,"version":"3.49.0"},"reference-count":45,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62236011"],"award-info":[{"award-number":["62236011"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Social Science Fund of China","award":["20&ZD279"],"award-info":[{"award-number":["20&ZD279"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Multimedia"],"published-print":{"date-parts":[[2024]]},"DOI":"10.1109\/tmm.2023.3277758","type":"journal-article","created":{"date-parts":[[2023,5,18]],"date-time":"2023-05-18T17:24:03Z","timestamp":1684430643000},"page":"1188-1199","source":"Crossref","is-referenced-by-count":10,"title":["Model-Guided Generative Adversarial Networks for Unsupervised Fine-Grained Image Generation"],"prefix":"10.1109","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6431-6205","authenticated-orcid":false,"given":"Jian","family":"Xiao","sequence":"first","affiliation":[{"name":"College of Information and Communication Engineering, Harbin Engineering University, Harbin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5382-1000","authenticated-orcid":false,"given":"Xiaojun","family":"Bi","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Minzu University of China, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","article-title":"Deep learning for fine-grained image analysis: A survey","author":"Wei","year":"2019"},{"key":"ref2","first-page":"2180","article-title":"InfoGAN: Interpretable representation learning by information maximizing generative adversarial nets","volume-title":"Proc. Conf. Neural Inf. Process. Syst.","author":"Chen","year":"2016"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2856256"},{"key":"ref4","article-title":"LR-GAN: Layered recursive generative adversarial networks for image generation","volume-title":"Proc. Int. Conf. Learn. Representation","author":"Yang","year":"2017"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58574-7_31"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00665"},{"key":"ref7","first-page":"2672","article-title":"Generative adversarial nets","volume-title":"Proc. Conf. Neural Inf. Process. Syst.","author":"Goodfellow","year":"2014"},{"key":"ref8","article-title":"Auto-encoding variational bayes","volume-title":"Proc. Int. Conf. Learn. Representation","author":"Kingma","year":"2014"},{"key":"ref9","article-title":"The caltech-ucsd birds-200-2011 dataset","author":"Wah","year":"2011"},{"key":"ref10","article-title":"Novel dataset for fine-grained image categorization","volume-title":"Proc. IEEE 1st Workshop Fine-Grained Vis. Categorization Conf. Comput. Vis. Pattern Recognit.","author":"Khosla","year":"2011"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2013.77"},{"key":"ref12","first-page":"2226","article-title":"Improved techniques for training GANs","volume-title":"Proc. Conf. Neural Inf. Process. Syst.","author":"Salimans","year":"2016"},{"key":"ref13","first-page":"6626","article-title":"GANs trained by a two time-scale update rule converge to a local NASH equilibrium","volume-title":"Proc. Conf. Neural Inf. Process. Syst.","author":"Heusel","year":"2017"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.299"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00806"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00913"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00143"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2019.2951463"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2020.107573"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2020.3026728"},{"key":"ref21","article-title":"Spectral normalization for generative adversarial networks","volume-title":"Proc. Int. Conf. Learn. Representation","author":"Miyato","year":"2018"},{"key":"ref22","article-title":"Large scale GAN training for high fidelity natural image synthesis","volume-title":"Proc. Int. Conf. Learn. Representation","author":"Brock","year":"2019"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00453"},{"key":"ref24","article-title":"Self-attention generative adversarial networks","volume-title":"Proc. 36th Int. Conf. Mach. Learn.","author":"Zhang","year":"2019"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00514"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2019.2922854"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2019.2959443"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2020.3045475"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01245"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1145\/1073204.1073274"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/1276377.1276382"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.278"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1145\/3072959.3073659"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00577"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2019.00408"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00457"},{"key":"ref37","article-title":"Multi-scale context aggregation by dilated convolutions","volume-title":"Proc. Int. Conf. Learn. Representation","author":"Yu","year":"2016"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46475-6_43"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.437"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.632"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.244"},{"key":"ref43","article-title":"Adam: A method for stochastic optimization","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Kingma","year":"2015"},{"key":"ref44","article-title":"A note on the inception score","author":"Barratt","year":"2018"},{"key":"ref45","first-page":"1","article-title":"Unsupervised representation learning with deep convolutional generative adversarial networks","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Radford","year":"2016"}],"container-title":["IEEE Transactions on Multimedia"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6046\/10384483\/10129077.pdf?arnumber=10129077","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,19]],"date-time":"2024-01-19T18:50:55Z","timestamp":1705690255000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10129077\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":45,"URL":"https:\/\/doi.org\/10.1109\/tmm.2023.3277758","relation":{},"ISSN":["1520-9210","1941-0077"],"issn-type":[{"value":"1520-9210","type":"print"},{"value":"1941-0077","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]}}}