{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T23:12:27Z","timestamp":1772233947459,"version":"3.50.1"},"reference-count":75,"publisher":"Springer Science and Business Media LLC","issue":"8","license":[{"start":{"date-parts":[[2021,4,2]],"date-time":"2021-04-02T00:00:00Z","timestamp":1617321600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,4,2]],"date-time":"2021-04-02T00:00:00Z","timestamp":1617321600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"crossref","award":["61972027"],"award-info":[{"award-number":["61972027"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. &amp; Cyber."],"published-print":{"date-parts":[[2021,8]]},"DOI":"10.1007\/s13042-021-01308-6","type":"journal-article","created":{"date-parts":[[2021,4,2]],"date-time":"2021-04-02T09:03:06Z","timestamp":1617354186000},"page":"2281-2295","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Imitating targets from all sides: an unsupervised transfer learning method for person re-identification"],"prefix":"10.1007","volume":"12","author":[{"given":"Jiajie","family":"Tian","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhu","family":"Teng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Baopeng","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanxue","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianping","family":"Fan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,4,2]]},"reference":[{"key":"1308_CR1","doi-asserted-by":"crossref","unstructured":"Ahmed E, Jones M, Marks TK (2015) An improved deep learning architecture for person re-identification. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 3908\u20133916","DOI":"10.1109\/CVPR.2015.7299016"},{"issue":"3","key":"1308_CR2","doi-asserted-by":"publisher","first-page":"1056","DOI":"10.1109\/TIP.2016.2514498","volume":"25","author":"S Bai","year":"2016","unstructured":"Bai S, Bai X (2016) Sparse contextual activation for efficient visual re-ranking. IEEE Trans Image Process 25(3):1056\u20131069","journal-title":"IEEE Trans Image Process"},{"key":"1308_CR3","unstructured":"Baktashmotlagh M, Faraki M, Drummond T, Salzmann M (2018) Learning factorized representations for open-set domain adaptation. arXiv preprint arXiv:180512277"},{"issue":"2","key":"1308_CR4","doi-asserted-by":"publisher","first-page":"130","DOI":"10.1016\/j.cviu.2012.10.008","volume":"117","author":"L Bazzani","year":"2013","unstructured":"Bazzani L, Cristani M, Murino V (2013) Symmetry-driven accumulation of local features for human characterization and re-identification. Comput Vis Image Underst 117(2):130\u2013144","journal-title":"Comput Vis Image Underst"},{"issue":"1\u20132","key":"1308_CR5","doi-asserted-by":"publisher","first-page":"151","DOI":"10.1007\/s10994-009-5152-4","volume":"79","author":"S Ben-David","year":"2010","unstructured":"Ben-David S, Blitzer J, Crammer K, Kulesza A, Pereira F, Vaughan JW (2010) A theory of learning from different domains. Mach Learn 79(1\u20132):151\u2013175","journal-title":"Mach Learn"},{"key":"1308_CR6","doi-asserted-by":"crossref","unstructured":"Chang X, Yang Y, Xiang T, Hospedales TM (2018) Disjoint label space transfer learning with common factorised space. arXiv preprint arXiv:181202605","DOI":"10.1609\/aaai.v33i01.33013288"},{"key":"1308_CR7","doi-asserted-by":"crossref","unstructured":"Chen W, Chen X, Zhang J, Huang K (2017) Beyond triplet loss: a deep quadruplet network for person re-identification. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 403\u2013412","DOI":"10.1109\/CVPR.2017.145"},{"key":"1308_CR8","doi-asserted-by":"crossref","unstructured":"Choi Y, Choi M, Kim M, Ha JW, Kim S, Choo J (2018) Stargan: Unified generative adversarial networks for multi-domain image-to-image translation. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 8789\u20138797","DOI":"10.1109\/CVPR.2018.00916"},{"key":"1308_CR9","doi-asserted-by":"crossref","unstructured":"Deng J, Dong W, Socher R, Li LJ, Li K, Fei-Fei L (2009) Imagenet: a large-scale hierarchical image database. In: 2009 IEEE conference on computer vision and pattern recognition, IEEE, pp 248\u2013255","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"1308_CR10","doi-asserted-by":"crossref","unstructured":"Deng W, Zheng L, Ye Q, Kang G, Yang Y, Jiao J (2018) Image\u2013image domain adaptation with preserved self-similarity and domain-dissimilarity for person re-identification. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 994\u20131003","DOI":"10.1109\/CVPR.2018.00110"},{"issue":"4","key":"1308_CR11","first-page":"83","volume":"14","author":"H Fan","year":"2018","unstructured":"Fan H, Zheng L, Yan C, Yang Y (2018) Unsupervised person re-identification: clustering and fine-tuning. ACM Trans Multimed Comput (TOMM) 14(4):83","journal-title":"ACM Trans Multimed Comput (TOMM)"},{"key":"1308_CR12","doi-asserted-by":"crossref","unstructured":"Farenzena M, Bazzani L, Perina A, Murino V, Cristani M (2010) Person re-identification by symmetry-driven accumulation of local features. In: 2010 IEEE Computer society conference on computer vision and pattern recognition, IEEE, pp 2360\u20132367","DOI":"10.1109\/CVPR.2010.5539926"},{"key":"1308_CR13","doi-asserted-by":"publisher","unstructured":"Feng Y, Yuan Y, Lu X (2021) Person re-identification via unsupervised cross-view metric learning. In: \u00a0IEEE Transactions on Cybernetics, vol 51, pp 1849\u20131859. https:\/\/doi.org\/10.1109\/TCYB.2019.2909480","DOI":"10.1109\/TCYB.2019.2909480"},{"issue":"9","key":"1308_CR14","doi-asserted-by":"publisher","first-page":"11631","DOI":"10.1007\/s11042-018-6654-5","volume":"78","author":"S Geng","year":"2019","unstructured":"Geng S, Yu M, Liu Y, Yu Y, Bai J (2019) Re-ranking pedestrian re-identification with multiple metrics. Multimed Tools Appl 78(9):11631\u201311653","journal-title":"Multimed Tools Appl"},{"key":"1308_CR15","doi-asserted-by":"crossref","unstructured":"Gray D, Tao H (2008) Viewpoint invariant pedestrian recognition with an ensemble of localized features. In: European conference on computer vision, Springer, pp 262\u2013275","DOI":"10.1007\/978-3-540-88682-2_21"},{"key":"1308_CR16","first-page":"5767","volume-title":"Improved training of wasserstein gans. In Advances in neural information processing systems","author":"I Gulrajani","year":"2017","unstructured":"Gulrajani I, Ahmed F, Arjovsky M, Dumoulin V, Courville AC (2017) Improved training of wasserstein gans. In Advances in neural information processing systems. Springer, New York, pp 5767\u20135777"},{"key":"1308_CR17","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 770\u2013778","DOI":"10.1109\/CVPR.2016.90"},{"key":"1308_CR18","first-page":"1","volume-title":"Deep feature embedding learning for person re-identification based on lifted structured loss. Multimedia tools and applications","author":"Z He","year":"2018","unstructured":"He Z, Cheolkon J, Qingtao F, Zhendong Z (2018) Deep feature embedding learning for person re-identification based on lifted structured loss. Multimedia tools and applications. Springer, New York, pp 1\u201318"},{"issue":"11","key":"1308_CR19","doi-asserted-by":"publisher","first-page":"5464","DOI":"10.1109\/TIP.2019.2916751","volume":"28","author":"Z He","year":"2019","unstructured":"He Z, Zuo W, Kan M, Shan S, Chen X (2019) Attgan: Facial attribute editing by only changing what you want. IEEE Trans Image Process 28(11):5464\u20135478","journal-title":"IEEE Trans Image Process"},{"key":"1308_CR20","doi-asserted-by":"crossref","unstructured":"Kalayeh MM, Basaran E, G\u00f6kmen M, Kamasak ME, Shah M (2018) Human semantic parsing for person re-identification. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 1062\u20131071","DOI":"10.1109\/CVPR.2018.00117"},{"key":"1308_CR21","unstructured":"Kingma DP, Ba J (2014) Adam: A method for stochastic optimization. arXiv preprint arXiv:14126980"},{"key":"1308_CR22","doi-asserted-by":"crossref","unstructured":"Kodirov E, Xiang T, Gong S (2015) Dictionary learning with iterative Laplacian regularisation for unsupervised person re-identification. In: BMVC, vol\u00a03, p\u00a08","DOI":"10.5244\/C.29.44"},{"issue":"17","key":"1308_CR23","doi-asserted-by":"publisher","first-page":"6989","DOI":"10.1007\/s11042-014-1949-7","volume":"74","author":"Q Leng","year":"2015","unstructured":"Leng Q, Hu R, Liang C, Wang Y, Chen J (2015) Person re-identification with content and context re-ranking. Multimed Tools Appl 74(17):6989\u20137014","journal-title":"Multimed Tools Appl"},{"key":"1308_CR24","doi-asserted-by":"crossref","unstructured":"Li W, Zhu X, Gong S (2018a) Harmonious attention network for person re-identification. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 2285\u20132294","DOI":"10.1109\/CVPR.2018.00243"},{"key":"1308_CR25","doi-asserted-by":"crossref","unstructured":"Li YJ, Yang FE, Liu YC, Yeh YY, Du X, Frank\u00a0Wang YC (2018b) Adaptation and re-identification network: an unsupervised deep transfer learning approach to person re-identification. In: Proceedings of the IEEE conference on computer vision and pattern recognition workshops, pp 172\u2013178","DOI":"10.1109\/CVPRW.2018.00054"},{"key":"1308_CR26","unstructured":"Lian Q, Li W, Chen L, Duan L (2019) Known-class aware self-ensemble for open set domain adaptation. arXiv preprint arXiv:190501068"},{"key":"1308_CR27","doi-asserted-by":"crossref","unstructured":"Liao S, Hu Y, Zhu X, Li SZ (2015) Person re-identification by local maximal occurrence representation and metric learning. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 2197\u20132206","DOI":"10.1109\/CVPR.2015.7298832"},{"key":"1308_CR28","unstructured":"Lin S, Li H, Li CT, Kot AC (2018) Multi-task mid-level feature alignment network for unsupervised cross-dataset person re-identification. arXiv preprint arXiv:180701440"},{"key":"1308_CR29","first-page":"1","volume":"2","author":"Y Lin","year":"2019","unstructured":"Lin Y, Dong X, Zheng L, Yan Y, Yang Y (2019) A bottom-up clustering approach to unsupervised person re-identification. Proc AAAI Conf Artif Intell 2:1\u20138","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"1308_CR30","doi-asserted-by":"crossref","unstructured":"Liu H, Cao Z, Long M, Wang J, Yang Q (2019) Separate to adapt: open set domain adaptation via progressive separation. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 2927\u20132936","DOI":"10.1109\/CVPR.2019.00304"},{"key":"1308_CR31","doi-asserted-by":"crossref","unstructured":"Liu X, Zhao H, Tian M, Sheng L, Shao J, Yi S, Yan J, Wang X (2017a) Hydraplus-net: attentive deep features for pedestrian analysis. In: Proceedings of the IEEE international conference on computer vision, pp 350\u2013359","DOI":"10.1109\/ICCV.2017.46"},{"key":"1308_CR32","doi-asserted-by":"crossref","unstructured":"Liu Z, Wang D, Lu H (2017b) Stepwise metric promotion for unsupervised video person re-identification. In: Proceedings of the IEEE international conference on computer vision, pp 2429\u20132438","DOI":"10.1109\/ICCV.2017.266"},{"key":"1308_CR33","unstructured":"Long M, Cao Y, Wang J, Jordan MI (2015) Learning transferable features with deep adaptation networks. arXiv preprint arXiv:150202791"},{"key":"1308_CR34","unstructured":"Long M, Zhu H, Wang J, Jordan MI (2017) Deep transfer learning with joint adaptation networks. In: Proceedings of the 34th International conference on machine learning, volume 70, JMLR. org, pp 2208\u20132217"},{"issue":"6\u20137","key":"1308_CR35","doi-asserted-by":"publisher","first-page":"379","DOI":"10.1016\/j.imavis.2014.04.002","volume":"32","author":"B Ma","year":"2014","unstructured":"Ma B, Su Y, Jurie F (2014) Covariance descriptor based on bio-inspired features for person re-identification and face verification. Image Vis Comput 32(6\u20137):379\u2013390","journal-title":"Image Vis Comput"},{"key":"1308_CR36","doi-asserted-by":"crossref","unstructured":"Panareda\u00a0Busto P, Gall J (2017) Open set domain adaptation. In: Proceedings of the IEEE international conference on computer vision, pp 754\u2013763","DOI":"10.1109\/ICCV.2017.88"},{"key":"1308_CR37","doi-asserted-by":"crossref","unstructured":"Peng P, Xiang T, Wang Y, Pontil M, Gong S, Huang T, Tian Y (2016) Unsupervised cross-dataset transfer learning for person re-identification. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 1306\u20131315","DOI":"10.1109\/CVPR.2016.146"},{"key":"1308_CR38","doi-asserted-by":"crossref","unstructured":"Ristani E, Solera F, Zou R, Cucchiara R, Tomasi C (2016) Performance measures and a data set for multi-target, multi-camera tracking. In: European conference on computer vision, Springer, pp 17\u201335","DOI":"10.1007\/978-3-319-48881-3_2"},{"key":"1308_CR39","first-page":"46","volume-title":"Transfer learning in a transductive setting. In Advances in neural information processing systems","author":"M Rohrbach","year":"2013","unstructured":"Rohrbach M, Ebert S, Schiele B (2013) Transfer learning in a transductive setting. In Advances in neural information processing systems. Springer, New York, pp 46\u201354"},{"key":"1308_CR40","doi-asserted-by":"crossref","unstructured":"Saito K, Yamamoto S, Ushiku Y, Harada T (2018) Open set domain adaptation by backpropagation. In: Proceedings of the European conference on computer vision (ECCV), pp 153\u2013168","DOI":"10.1007\/978-3-030-01228-1_10"},{"key":"1308_CR41","first-page":"2110","volume-title":"Learning transferrable representations for unsupervised domain adaptation. In Advances in neural information processing systems","author":"O Sener","year":"2016","unstructured":"Sener O, Song HO, Saxena A, Savarese S (2016) Learning transferrable representations for unsupervised domain adaptation. In Advances in neural information processing systems. Springer, New York, pp 2110\u20132118"},{"key":"1308_CR42","unstructured":"Shu R, Bui HH, Narui H, Ermon S (2018) A dirt-t approach to unsupervised domain adaptation. arXiv preprint arXiv:180208735"},{"key":"1308_CR43","doi-asserted-by":"crossref","unstructured":"Sun Y, Zheng L, Yang Y, Tian Q, Wang S (2018) Beyond part models: person retrieval with refined part pooling (and a strong convolutional baseline). In: The European conference on computer vision (ECCV)","DOI":"10.1007\/978-3-030-01225-0_30"},{"key":"1308_CR44","doi-asserted-by":"crossref","unstructured":"Tan S, Jiao J, Zheng WS (2019) Weakly supervised open-set domain adaptation by dual-domain collaboration. arXiv preprint arXiv:190413179","DOI":"10.1109\/CVPR.2019.00554"},{"key":"1308_CR45","unstructured":"Tzeng E, Hoffman J, Zhang N, Saenko K, Darrell T (2014) Deep domain confusion: maximizing for domain invariance. arXiv preprint arXiv:14123474"},{"key":"1308_CR46","doi-asserted-by":"crossref","unstructured":"Tzeng E, Hoffman J, Saenko K, Darrell T (2017) Adversarial discriminative domain adaptation. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 7167\u20137176","DOI":"10.1109\/CVPR.2017.316"},{"key":"1308_CR47","doi-asserted-by":"crossref","unstructured":"Wang F, Zuo W, Lin L, Zhang D, Zhang L (2016a) Joint learning of single-image and cross-image representations for person re-identification. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 1288\u20131296","DOI":"10.1109\/CVPR.2016.144"},{"key":"1308_CR48","doi-asserted-by":"crossref","unstructured":"Wang G, Lin L, Ding S, Li Y, Wang Q (2016b) Dari: distance metric and representation integration for person verification. In: Thirtieth AAAI conference on artificial intelligence","DOI":"10.1609\/aaai.v30i1.10462"},{"key":"1308_CR49","doi-asserted-by":"crossref","unstructured":"Wang H, Gong S, Xiang T (2014a) Unsupervised learning of generative topic saliency for person re-identification. In: Proceedings of the British machine vision conference (BMVC)","DOI":"10.5244\/C.28.48"},{"key":"1308_CR50","doi-asserted-by":"crossref","unstructured":"Wang J, Zhu X, Gong S, Li W (2018) Transferable joint attribute-identity deep learning for unsupervised person re-identification. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 2275\u20132284","DOI":"10.1109\/CVPR.2018.00242"},{"issue":"9","key":"1308_CR51","doi-asserted-by":"publisher","first-page":"4376","DOI":"10.1109\/TIP.2019.2910667","volume":"28","author":"Q Wang","year":"2019","unstructured":"Wang Q, Gao J, Li X (2019a) Weakly supervised adversarial domain adaptation for semantic segmentation in urban scenes. IEEE Trans Image Process 28(9):4376\u20134386","journal-title":"IEEE Trans Image Process"},{"key":"1308_CR52","doi-asserted-by":"crossref","unstructured":"Wang Q, Gao J, Lin W, Yuan Y (2019b) Learning from synthetic data for crowd counting in the wild. In: The IEEE conference on computer vision and pattern recognition (CVPR)","DOI":"10.1109\/CVPR.2019.00839"},{"key":"1308_CR53","doi-asserted-by":"crossref","unstructured":"Wang T, Gong S, Zhu X, Wang S (2014b) Person re-identification by video ranking. In: European conference on computer vision, Springer, pp 688\u2013703","DOI":"10.1007\/978-3-319-10593-2_45"},{"key":"1308_CR54","doi-asserted-by":"crossref","unstructured":"Wei L, Zhang S, Gao W, Tian Q (2018a) Person transfer gan to bridge domain gap for person re-identification. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 79\u201388","DOI":"10.1109\/CVPR.2018.00016"},{"issue":"4","key":"1308_CR55","doi-asserted-by":"publisher","first-page":"986","DOI":"10.1109\/TMM.2018.2870522","volume":"21","author":"L Wei","year":"2018","unstructured":"Wei L, Zhang S, Yao H, Gao W, Tian Q (2018b) Glad: Global-local-alignment descriptor for scalable person re-identification. IEEE Trans Multimed 21(4):986\u2013999","journal-title":"IEEE Trans Multimed"},{"key":"1308_CR56","doi-asserted-by":"crossref","unstructured":"Wu PW, Lin YJ, Chang CH, Chang EY, Liao SW (2019a) Relgan: Multi-domain image-to-image translation via relative attributes. In: Proceedings of the IEEE international conference on computer vision, pp 5914\u20135922","DOI":"10.1109\/ICCV.2019.00601"},{"key":"1308_CR57","doi-asserted-by":"crossref","unstructured":"Wu Y, Lin Y, Dong X, Yan Y, Ouyang W, Yang Y (2018) Exploit the unknown gradually: one-shot video-based person re-identification by stepwise learning. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 5177\u20135186","DOI":"10.1109\/CVPR.2018.00543"},{"issue":"6","key":"1308_CR58","doi-asserted-by":"publisher","first-page":"2872","DOI":"10.1109\/TIP.2019.2891895","volume":"28","author":"Y Wu","year":"2019","unstructured":"Wu Y, Lin Y, Dong X, Yan Y, Bian W, Yang Y (2019b) Progressive learning for person re-identification with one example. IEEE Trans Image Process 28(6):2872\u20132881","journal-title":"IEEE Trans Image Process"},{"key":"1308_CR59","doi-asserted-by":"crossref","unstructured":"Xiao T, Li H, Ouyang W, Wang X (2016) Learning deep feature representations with domain guided dropout for person re-identification. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 1249\u20131258","DOI":"10.1109\/CVPR.2016.140"},{"issue":"12","key":"1308_CR60","doi-asserted-by":"publisher","first-page":"3150","DOI":"10.1109\/TNNLS.2015.2405574","volume":"26","author":"X Xu","year":"2015","unstructured":"Xu X, Li W, Xu D (2015) Distance metric learning using privileged information for face verification and person re-identification. IEEE Trans Neural Netw Learn Syst 26(12):3150\u20133162","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"12","key":"1308_CR61","doi-asserted-by":"publisher","first-page":"2553","DOI":"10.1109\/TMM.2016.2605058","volume":"18","author":"M Ye","year":"2016","unstructured":"Ye M, Liang C, Yu Y, Wang Z, Leng Q, Xiao C, Chen J, Hu R (2016) Person reidentification via ranking aggregation of similarity pulling and dissimilarity pushing. IEEE Trans Multimed 18(12):2553\u20132566","journal-title":"IEEE Trans Multimed"},{"key":"1308_CR62","doi-asserted-by":"crossref","unstructured":"Ye M, Ma AJ, Zheng L, Li J, Yuen PC (2017) Dynamic label graph matching for unsupervised video re-identification. In: Proceedings of the IEEE international conference on computer vision, pp 5142\u20135150","DOI":"10.1109\/ICCV.2017.550"},{"key":"1308_CR63","doi-asserted-by":"crossref","unstructured":"Yu HX, Wu A, Zheng WS (2017) Cross-view asymmetric metric learning for unsupervised person re-identification. In: Proceedings of the IEEE international conference on computer vision, pp 994\u20131002","DOI":"10.1109\/ICCV.2017.113"},{"key":"1308_CR64","doi-asserted-by":"crossref","unstructured":"Yu HX, Zheng WS, Wu A, Guo X, Gong S, Lai JH (2019) Unsupervised person re-identification by soft multilabel learning. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 2148\u20132157","DOI":"10.1109\/CVPR.2019.00225"},{"key":"1308_CR65","doi-asserted-by":"publisher","first-page":"387","DOI":"10.1016\/j.neucom.2019.10.083","volume":"378","author":"Y Yuan","year":"2020","unstructured":"Yuan Y, Zhang J, Wang Q (2020) Deep Gabor convolution network for person re-identification. Neurocomputing 378:387\u2013398","journal-title":"Neurocomputing"},{"key":"1308_CR66","doi-asserted-by":"crossref","unstructured":"Zhao R, Ouyang W, Wang X (2014) Learning mid-level filters for person re-identification. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 144\u2013151","DOI":"10.1109\/CVPR.2014.26"},{"issue":"2","key":"1308_CR67","doi-asserted-by":"publisher","first-page":"356","DOI":"10.1109\/TPAMI.2016.2544310","volume":"39","author":"R Zhao","year":"2017","unstructured":"Zhao R, Oyang W, Wang X (2017) Person re-identification by saliency learning. IEEE Trans Pattern Anal Mach Intell 39(2):356\u2013370. https:\/\/doi.org\/10.1109\/TPAMI.2016.2544310","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"1308_CR68","doi-asserted-by":"crossref","unstructured":"Zheng L, Shen L, Tian L, Wang S, Wang J, Tian Q (2015) Scalable person re-identification: a benchmark. In: Proceedings of the IEEE international conference on computer vision, pp 1116\u20131124","DOI":"10.1109\/ICCV.2015.133"},{"key":"1308_CR69","unstructured":"Zheng L, Yang Y, Hauptmann AG (2016) Person re-identification: past, present and future. arXiv preprint arXiv:161002984"},{"key":"1308_CR70","doi-asserted-by":"crossref","unstructured":"Zheng Z, Zheng L, Yang Y (2017) Unlabeled samples generated by gan improve the person re-identification baseline in vitro. In: Proceedings of the IEEE international conference on computer vision, pp 3754\u20133762","DOI":"10.1109\/ICCV.2017.405"},{"key":"1308_CR71","doi-asserted-by":"crossref","unstructured":"Zhong Z, Zheng L, Cao D, Li S (2017) Re-ranking person re-identification with k-reciprocal encoding. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 1318\u20131327","DOI":"10.1109\/CVPR.2017.389"},{"key":"1308_CR72","doi-asserted-by":"crossref","unstructured":"Zhong Z, Zheng L, Li S, Yang Y (2018a) Generalizing a person retrieval model hetero-and homogeneously. In: Proceedings of the European conference on computer vision (ECCV), pp 172\u2013188","DOI":"10.1007\/978-3-030-01261-8_11"},{"key":"1308_CR73","doi-asserted-by":"crossref","unstructured":"Zhong Z, Zheng L, Zheng Z, Li S, Yang Y (2018b) Camera style adaptation for person re-identification. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 5157\u20135166","DOI":"10.1109\/CVPR.2018.00541"},{"key":"1308_CR74","doi-asserted-by":"crossref","unstructured":"Zhong Z, Zheng L, Luo Z, Li S, Yang Y (2019) Invariance matters: exemplar memory for domain adaptive person re-identification. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 598\u2013607","DOI":"10.1109\/CVPR.2019.00069"},{"key":"1308_CR75","doi-asserted-by":"crossref","unstructured":"Zhu JY, Park T, Isola P, Efros AA (2017) Unpaired image-to-image translation using cycle-consistent adversarial networks. In: Proceedings of the IEEE international conference on computer vision, pp 2223\u20132232","DOI":"10.1109\/ICCV.2017.244"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-021-01308-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13042-021-01308-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-021-01308-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,23]],"date-time":"2022-12-23T06:39:11Z","timestamp":1671777551000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13042-021-01308-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,4,2]]},"references-count":75,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2021,8]]}},"alternative-id":["1308"],"URL":"https:\/\/doi.org\/10.1007\/s13042-021-01308-6","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"value":"1868-8071","type":"print"},{"value":"1868-808X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,4,2]]},"assertion":[{"value":"13 March 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 March 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 April 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}