{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T04:37:27Z","timestamp":1780634247841,"version":"3.54.1"},"reference-count":50,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"4","license":[{"start":{"date-parts":[[2021,10,1]],"date-time":"2021-10-01T00:00:00Z","timestamp":1633046400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,10,1]],"date-time":"2021-10-01T00:00:00Z","timestamp":1633046400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,10,1]],"date-time":"2021-10-01T00:00:00Z","timestamp":1633046400000},"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 Robot. Autom. Lett."],"published-print":{"date-parts":[[2021,10]]},"DOI":"10.1109\/lra.2021.3095311","type":"journal-article","created":{"date-parts":[[2021,7,7]],"date-time":"2021-07-07T20:08:20Z","timestamp":1625688500000},"page":"6931-6938","source":"Crossref","is-referenced-by-count":33,"title":["Unsupervised Image Segmentation by Mutual Information Maximization and Adversarial Regularization"],"prefix":"10.1109","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9678-0811","authenticated-orcid":false,"given":"S. Ehsan","family":"Mirsadeghi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ali","family":"Royat","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8659-8773","authenticated-orcid":false,"given":"Hamid","family":"Rezatofighi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","article-title":"Discriminative Clustering by Regularized Information Maximization","author":"krause","year":"2010","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10578-9_23"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00066"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01234-2_22"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2012.120"},{"key":"ref30","article-title":"Unsupervised object segmentation by redrawing","author":"chen","year":"2019","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref37","article-title":"Unsupervised data augmentation for consistency training","author":"xie","year":"2020","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref36","article-title":"The effectiveness of data augmentation in image classification using deep learning","author":"perez","year":"2017"},{"key":"ref35","first-page":"91","article-title":"Faster R-Cnn: Towards real-time object detection with region proposal networks","volume":"28","author":"ren","year":"2015","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref34","first-page":"13964","article-title":"Superpixel segmentation with fully convolutional networks","author":"yang","year":"2020","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit"},{"key":"ref28","first-page":"3861","article-title":"Towards K-means-friendly spaces: Simultaneous deep learning and clustering","author":"yang","year":"2017","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref27","first-page":"849","article-title":"On spectral clustering: Analysis and an algorithm","author":"ng","year":"2001","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref29","article-title":"Emergence of object segmentation in perturbed generative models","author":"bielski","year":"2019","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.549"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2699184"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58571-6_9"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3059968"},{"key":"ref21","year":"0","journal-title":"ISPRS 2d semantic labeling contest"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2013.378"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00326"},{"key":"ref26","first-page":"1537","article-title":"Maximum margin clustering","author":"xu","year":"2004","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref25","author":"mclachlan","year":"1988","journal-title":"Mixture Models Inference and Applications to Clustering"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1002\/nav.3800020109"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/273"},{"key":"ref11","first-page":"2180","article-title":"Infogan: Interpretable representation learning by information maximizing generative adversarial nets","author":"chen","year":"2016","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1214\/aoms\/1177729694"},{"key":"ref12","first-page":"1558","article-title":"Learning discrete representations via information maximizing self-augmented training","author":"hu","year":"2017","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.612"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.556"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.626"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00132"},{"key":"ref17","article-title":"W-Net: A deep model for fully unsupervised image segmentation","author":"xia","year":"2017"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00996"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00743"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.660"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.2983686"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01264-9_9"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"ref8","first-page":"740","article-title":"Microsoft Coco: Common objects in context","author":"lin","year":"2014","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.81"},{"key":"ref49","article-title":"Pytorch: An Open Source Machine Learning Framework","author":"paszke","year":"0"},{"key":"ref9","first-page":"478","article-title":"Unsupervised deep embedding for clustering analysis","author":"xie","year":"2016","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref46","article-title":"Learning visual groups from co-occurrences in space and time","author":"isola","year":"2015"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.167"},{"key":"ref48","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2015","journal-title":"Proc 3rd Int Conf for Learn Representations"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01264-9_9"},{"key":"ref42","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 Interv"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46484-8_29"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1023\/B:VISI.0000029664.99615.94"},{"key":"ref43","first-page":"2825","article-title":"Scikit-learn: Machine learning in python","volume":"12","author":"pedregosa","year":"2011","journal-title":"J Mach Learn Res"}],"container-title":["IEEE Robotics and Automation Letters"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7083369\/9475905\/09476978.pdf?arnumber=9476978","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T14:54:08Z","timestamp":1652194448000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9476978\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10]]},"references-count":50,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.1109\/lra.2021.3095311","relation":{},"ISSN":["2377-3766","2377-3774"],"issn-type":[{"value":"2377-3766","type":"electronic"},{"value":"2377-3774","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,10]]}}}