{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T07:35:24Z","timestamp":1763105724801},"reference-count":78,"publisher":"Springer Science and Business Media LLC","issue":"31-32","license":[{"start":{"date-parts":[[2020,5,25]],"date-time":"2020-05-25T00:00:00Z","timestamp":1590364800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,5,25]],"date-time":"2020-05-25T00:00:00Z","timestamp":1590364800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61673274"],"award-info":[{"award-number":["61673274"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shanghai Science and Technology Commission Scientific Research Project","award":["17DZ1100803"],"award-info":[{"award-number":["17DZ1100803"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2020,8]]},"DOI":"10.1007\/s11042-019-08395-2","type":"journal-article","created":{"date-parts":[[2020,5,25]],"date-time":"2020-05-25T14:03:10Z","timestamp":1590415390000},"page":"22525-22549","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["A part-based attention network for person re-identification"],"prefix":"10.1007","volume":"79","author":[{"given":"Weilin","family":"Zhong","sequence":"first","affiliation":[]},{"given":"Linfeng","family":"Jiang","sequence":"additional","affiliation":[]},{"given":"Tao","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Jinsheng","family":"Ji","sequence":"additional","affiliation":[]},{"given":"Huilin","family":"Xiong","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,5,25]]},"reference":[{"key":"8395_CR1","doi-asserted-by":"crossref","unstructured":"Ahmed E, Jones M, Marks TK (2015) An improved deep learning architecture for person re-identification. In: IEEE conference on computer vision and pattern recognition, pp 3908\u20133916","DOI":"10.1109\/CVPR.2015.7299016"},{"key":"8395_CR2","doi-asserted-by":"crossref","unstructured":"Cao Z, Simon T, Wei SE, Sheikh Y (2017) Realtime multi-person 2d pose estimation using part affinity fields. In: IEEE conference on computer vision and pattern recognition, pp 1302\u20131310","DOI":"10.1109\/CVPR.2017.143"},{"key":"8395_CR3","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: IEEE conference on computer vision and pattern recognition, pp 403\u2013412","DOI":"10.1109\/CVPR.2017.145"},{"key":"8395_CR4","doi-asserted-by":"crossref","unstructured":"Chen Y, Zhu X, Gong S (2018) Person re-identification by deep learning multi-scale representations. In: IEEE international conference on computer vision workshop, pp 2590\u20132600","DOI":"10.1109\/ICCVW.2017.304"},{"key":"8395_CR5","doi-asserted-by":"crossref","unstructured":"Cheng D, Gong Y, Zhou S, Wang J, Zheng N (2016) Person re-identification by multi-channel parts-based cnn with improved triplet loss function. In: IEEE conference on computer vision and pattern recognition, pp 1335\u20131344","DOI":"10.1109\/CVPR.2016.149"},{"key":"8395_CR6","doi-asserted-by":"crossref","unstructured":"Davis JV, Kulis B, Jain P, Sra S, Dhillon IS (2007) Information-theoretic metric learning. In: International conference on machine learning, pp 209\u2013216","DOI":"10.1145\/1273496.1273523"},{"issue":"10","key":"8395_CR7","doi-asserted-by":"publisher","first-page":"2993","DOI":"10.1016\/j.patcog.2015.04.005","volume":"48","author":"S Ding","year":"2015","unstructured":"Ding S, Lin L, Wang G, Chao H (2015) Deep feature learning with relative distance comparison for person re-identification. Pattern Recogn 48(10):2993\u20133003","journal-title":"Pattern Recogn"},{"key":"8395_CR8","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: IEEE conference on computer vision and pattern recognition, pp 2360\u20132367","DOI":"10.1109\/CVPR.2010.5539926"},{"issue":"9","key":"8395_CR9","doi-asserted-by":"publisher","first-page":"1627","DOI":"10.1109\/TPAMI.2009.167","volume":"32","author":"PF Felzenszwalb","year":"2010","unstructured":"Felzenszwalb PF, Girshick RB, McAllester D, Ramanan D (2010) Object detection with discriminatively trained part-based models. IEEE Trans Pattern Anal Mach Intell 32(9):1627\u20131645","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"8395_CR10","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, pp 262\u2013275","DOI":"10.1007\/978-3-540-88682-2_21"},{"issue":"26","key":"8395_CR11","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1016\/j.neucom.2015.09.116","volume":"187","author":"Y Guo","year":"2016","unstructured":"Guo Y, Yu L, Oerlemans A, Lao S, Song W, Lew MS (2016) Deep learning for visual understanding: a review. Neurocomputing 187(26):27\u201348","journal-title":"Neurocomputing"},{"key":"8395_CR12","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition. In: IEEE conference on computer vision and pattern recognition, pp 770\u2013778","DOI":"10.1109\/CVPR.2016.90"},{"key":"8395_CR13","unstructured":"Hermans A, Beyer L, Leibe B (2017) In defense of the triplet loss for person re-identification. arXiv:1703.07737"},{"key":"8395_CR14","doi-asserted-by":"crossref","unstructured":"Hirzer M, Roth PM, Bischof H (2012) Person re-identification by efficient impostor-based metric learning. In: International conference on advanced video and signal-based surveillance, pp 203\u2013208","DOI":"10.1109\/AVSS.2012.55"},{"key":"8395_CR15","doi-asserted-by":"crossref","unstructured":"Hu J, Shen L, Sun G (2018) Squeeze-and-excitation networks. In: IEEE conference on computer vision and pattern recognition, pp 7132\u20137141","DOI":"10.1109\/CVPR.2018.00745"},{"key":"8395_CR16","unstructured":"Jaderberg M, Simonyan K, Zisserman A, et al. (2015) Spatial transformer networks. In: Neural information processing systems, pp 2017\u20132025"},{"key":"8395_CR17","doi-asserted-by":"crossref","unstructured":"Khamis S, Kuo CH, Singh VK, Shet VD, Davis LS (2014) Joint learning for attribute-consistent person re-identification. In: European conference on computer vision, pp 134\u2013146","DOI":"10.1007\/978-3-319-16199-0_10"},{"key":"8395_CR18","doi-asserted-by":"crossref","unstructured":"Koestinger M, Hirzer M, Wohlhart P, Roth PM, Bischof H (2012) Large scale metric learning from equivalence constraints. In: IEEE conference on computer vision and pattern recognition, pp 2288\u20132295","DOI":"10.1109\/CVPR.2012.6247939"},{"key":"8395_CR19","unstructured":"Krizhevsky A, Sutskever I, Hinton GE (2012) Imagenet classification with deep convolutional neural networks. In: Neural information processing systems, pp 1097\u20131105"},{"issue":"7","key":"8395_CR20","doi-asserted-by":"publisher","first-page":"1622","DOI":"10.1109\/TPAMI.2012.246","volume":"35","author":"I Kviatkovsky","year":"2013","unstructured":"Kviatkovsky I, Adam A, Rivlin E (2013) Color invariants for person reidentification. IEEE Trans Pattern Anal Mach Intell 35(7):1622\u201334","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"8395_CR21","doi-asserted-by":"crossref","unstructured":"Li D, Chen X, Zhang Z, Huang K (2017) Learning deep context-aware features over body and latent parts for person re-identification. In: IEEE conference on computer vision and pattern recognition, pp 384\u2013393","DOI":"10.1109\/CVPR.2017.782"},{"key":"8395_CR22","doi-asserted-by":"crossref","unstructured":"Li W, Wang X (2013) Locally aligned feature transforms across views. In: IEEE conference on computer vision and pattern recognition, pp 3594\u20133601","DOI":"10.1109\/CVPR.2013.461"},{"key":"8395_CR23","doi-asserted-by":"crossref","unstructured":"Li W, Zhao R, Wang X (2012) Human reidentification with transferred metric learning. In: Asian conference on computer vision, pp 31\u201344","DOI":"10.1007\/978-3-642-37331-2_3"},{"key":"8395_CR24","doi-asserted-by":"crossref","unstructured":"Li W, Zhao R, Xiao T, Wang X (2014) Deepreid: deep filter pairing neural network for person re-identification. In: IEEE conference on computer vision and pattern recognition, pp 152\u2013159","DOI":"10.1109\/CVPR.2014.27"},{"key":"8395_CR25","doi-asserted-by":"crossref","unstructured":"Li W, Zhu X, Gong S (2017) Person re-identification by deep joint learning of multi-loss classification. In: International joint conference on artificial intelligence, pp 2194\u20132200","DOI":"10.24963\/ijcai.2017\/305"},{"key":"8395_CR26","doi-asserted-by":"crossref","unstructured":"Li W, Zhu X, Gong S (2018) Harmonious attention network for person re-identification. In: IEEE conference on computer vision and pattern recognition, pp 2285\u20132294","DOI":"10.1109\/CVPR.2018.00243"},{"key":"8395_CR27","doi-asserted-by":"crossref","unstructured":"Liao S, Hu Y, Zhu X, Li S (2015) Person re-identification by local maximal occurrence representation and metric learning. In: IEEE conference on computer vision and pattern recognition, pp 2197\u20132206","DOI":"10.1109\/CVPR.2015.7298832"},{"key":"8395_CR28","unstructured":"Lin Y, Zheng L, Zheng Z, Wu Y, Yang Y (2017) Improving person re-identification by attribute and identity learning. arXiv:1703.07220"},{"issue":"7","key":"8395_CR29","doi-asserted-by":"publisher","first-page":"3492","DOI":"10.1109\/TIP.2017.2700762","volume":"26","author":"H Liu","year":"2017","unstructured":"Liu H, Feng J, Qi M, Jiang J, Yan S (2017) End-to-end comparative attention networks for person re-identification. IEEE Trans Image Process 26(7):3492\u20133506","journal-title":"IEEE Trans Image Process"},{"key":"8395_CR30","doi-asserted-by":"crossref","unstructured":"Mignon A, Jurie F (2012) Pcca: a new approach for distance learning from sparse pairwise constraints. In: IEEE conference on computer vision and pattern recognition, pp 2666\u20132672","DOI":"10.1109\/CVPR.2012.6247987"},{"issue":"3","key":"8395_CR31","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1068\/p2896","volume":"30","author":"H Moon","year":"2001","unstructured":"Moon H, Phillips PJ (2001) Computational and performance aspects of pca-based face-recognition algorithms. Perception 30(3):303\u201321","journal-title":"Perception"},{"key":"8395_CR32","doi-asserted-by":"crossref","unstructured":"Pedagadi S, Orwell J, Velastin S, Boghossian B (2013) Local fisher discriminant analysis for pedestrian re-identification. In: IEEE conference on computer vision and pattern recognition, pp 3318\u20133325","DOI":"10.1109\/CVPR.2013.426"},{"key":"8395_CR33","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, pp 17\u201335","DOI":"10.1007\/978-3-319-48881-3_2"},{"issue":"3","key":"8395_CR34","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1007\/s11263-015-0816-y","volume":"115","author":"O Russakovsky","year":"2014","unstructured":"Russakovsky O, Deng J, Su H, Krause J, Satheesh S, Ma S, Huang Z, Karpathy A, Khosla A, Bernstein M (2014) Imagenet large scale visual recognition challenge. Int J Comput Vis 115(3):211\u2013252","journal-title":"Int J Comput Vis"},{"key":"8395_CR35","doi-asserted-by":"crossref","unstructured":"Sarfraz MS, Schumann A, Eberle A, Stiefelhagen R (2018) A pose-sensitive embedding for person re-identification with expanded cross neighborhood re-ranking. In: IEEE international conference on computer vision, pp 420\u2013429","DOI":"10.1109\/CVPR.2018.00051"},{"key":"8395_CR36","doi-asserted-by":"crossref","unstructured":"Schumann A, Stiefelhagen R (2017) Person re-identification by deep learning attribute-complementary information. In: IEEE conference on computer vision and pattern recognition workshops, pp 1435\u20131443","DOI":"10.1109\/CVPRW.2017.186"},{"key":"8395_CR37","unstructured":"Sharma S, Kiros R, Salakhutdinov R (2015) Action recognition using visual attention. arXiv:1511.04119"},{"key":"8395_CR38","doi-asserted-by":"crossref","unstructured":"Shi H, Yang Y, Zhu X, Liao S, Lei Z, Zheng W, Li S (2016) Embedding deep metric for person re-identification: a study against large variations. In: European conference on computer vision, pp 732\u2013748","DOI":"10.1007\/978-3-319-46448-0_44"},{"key":"8395_CR39","doi-asserted-by":"crossref","unstructured":"Si J, Zhang H, Li C, Kuen J, Kong X, Kot AC, Wang G (2018) Dual attention matching network for context-aware feature sequence based person re-identification. In: IEEE conference on computer vision and pattern recognition, pp 5363\u20135372","DOI":"10.1109\/CVPR.2018.00562"},{"key":"8395_CR40","unstructured":"Simonyan K, Zisserman A (2015) Very deep convolutional networks for large-scale image recognition. In: International conference on learning representations"},{"key":"8395_CR41","doi-asserted-by":"crossref","unstructured":"Su C, Li J, Zhang S, Xing J, Gao W, Tian Q (2017) Pose-driven deep convolutional model for person re-identification. In: IEEE international conference on computer vision, pp 3960\u20133969","DOI":"10.1109\/ICCV.2017.427"},{"key":"8395_CR42","doi-asserted-by":"crossref","unstructured":"Sun Y, Zheng L, Deng W, Wang S (2017) Svdnet for pedestrian retrieval. In: IEEE international conference on computer vision, pp 3820\u20133828","DOI":"10.1109\/ICCV.2017.410"},{"key":"8395_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: European conference on computer vision, pp 501\u2013518","DOI":"10.1007\/978-3-030-01225-0_30"},{"key":"8395_CR44","doi-asserted-by":"crossref","unstructured":"Varior RR, Haloi M, Wang G (2016) Gated siamese convolutional neural network architecture for human re-identification. In: European conference on computer vision, pp 791\u2013808","DOI":"10.1007\/978-3-319-46484-8_48"},{"key":"8395_CR45","doi-asserted-by":"crossref","unstructured":"Varior RR, Shuai B, Lu J, Xu D, Wang G (2016) A siamese long short-term memory architecture for human re-identification. In: European conference on computer vision, pp 135\u2013153","DOI":"10.1007\/978-3-319-46478-7_9"},{"key":"8395_CR46","first-page":"1","volume":"2018","author":"A Voulodimos","year":"2018","unstructured":"Voulodimos A, Doulamis N, Doulamis A, Protopapadakis E (2018) Deep learning for computer vision: a brief review. Comput Intell Neurosci 2018:1\u201313","journal-title":"Comput Intell Neurosci"},{"key":"8395_CR47","doi-asserted-by":"crossref","unstructured":"Wang C, Zhang Q, Huang C, Liu W, Wang X (2018) Mancs: a multi-task attentional network with curriculum sampling for person re-identification. In: European conference on computer vision, pp 365\u2013381","DOI":"10.1007\/978-3-030-01225-0_23"},{"key":"8395_CR48","doi-asserted-by":"crossref","unstructured":"Wang F, Jiang M, Qian C, Yang S, Li C, Zhang H, Wang X, Tang X (2017) Residual attention network for image classification. In: IEEE conference on computer vision and pattern recognition, pp 6450\u20136458","DOI":"10.1109\/CVPR.2017.683"},{"key":"8395_CR49","doi-asserted-by":"crossref","unstructured":"Wang F, Zuo W, Lin L, Zhang D, Zhang L (2016) Joint learning of single-image and cross-image representations for person re-identification. In: IEEE conference on computer vision and pattern recognition, pp 1288\u20131296","DOI":"10.1109\/CVPR.2016.144"},{"key":"8395_CR50","doi-asserted-by":"crossref","unstructured":"Wang Y, Wang L, You Y, Zou X, Chen V, Li S, Huang G, Hariharan B, Weinberger KQ (2018) Resource aware person re-identification across multiple resolutions. In: IEEE conference on computer vision and pattern recognition, pp 8042\u20138051","DOI":"10.1109\/CVPR.2018.00839"},{"key":"8395_CR51","doi-asserted-by":"crossref","unstructured":"Wei SE, Ramakrishna V, Kanade T, Sheikh Y (2016) Convolutional pose machines. In: IEEE conference on computer vision and pattern recognition, pp 4724\u20134732","DOI":"10.1109\/CVPR.2016.511"},{"issue":"1","key":"8395_CR52","first-page":"207","volume":"10","author":"KQ Weinberger","year":"2009","unstructured":"Weinberger KQ, Saul LK (2009) Distance metric learning for large margin nearest neighbor classification. J Mach Learn Res 10(1):207\u2013244","journal-title":"J Mach Learn Res"},{"key":"8395_CR53","doi-asserted-by":"crossref","unstructured":"Woo S, Park J, Lee JY, Kweon IS (2018) Cbam: convolutional block attention module. In: European conference on computer vision, pp 3\u201319","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"8395_CR54","unstructured":"Wu L, Shen C, Hengel AVD (2016) Personnet: person re-identification with deep convolutional neural networks. arXiv:1601.07255"},{"key":"8395_CR55","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: IEEE conference on computer vision and pattern recognition, pp 1249\u20131258","DOI":"10.1109\/CVPR.2016.140"},{"key":"8395_CR56","doi-asserted-by":"crossref","unstructured":"Xiao T, Li S, Wang B, Lin L, Wang X (2017) Joint detection and identification feature learning for person search. In: IEEE conference on computer vision and pattern recognition, pp 3376\u20133385","DOI":"10.1109\/CVPR.2017.360"},{"key":"8395_CR57","doi-asserted-by":"crossref","unstructured":"Xiong F, Gou M, Camps O, Sznaier M (2014) Person re-identification using kernel-based metric learning methods. In: European conference on computer vision, pp 1\u201316","DOI":"10.1007\/978-3-319-10584-0_1"},{"key":"8395_CR58","unstructured":"Xiong F, Xiao Y, Cao Z, Gong K, Fang Z, Zhou JT (2018) Towards good practices on building effective cnn baseline model for person re-identification. arXiv:1807.11042"},{"key":"8395_CR59","doi-asserted-by":"crossref","unstructured":"Xu J, Zhao R, Zhu F, Wang H, Ouyang W (2018) Attention-aware compositional network for person re-identification. In: IEEE conference on computer vision and pattern recognition, pp 2119\u20132128","DOI":"10.1109\/CVPR.2018.00226"},{"key":"8395_CR60","doi-asserted-by":"crossref","unstructured":"Yang Y, Yang J, Yan J, Liao S, Yi D, Li S (2014) Salient color names for person re-identification. In: European conference on computer vision, pp 536\u2013551","DOI":"10.1007\/978-3-319-10590-1_35"},{"key":"8395_CR61","doi-asserted-by":"crossref","unstructured":"Yi D, Lei Z, Liao S, Li S (2014) Deep metric learning for person re-identification. In: International conference on pattern recognition, pp 34\u201339","DOI":"10.1109\/ICPR.2014.16"},{"key":"8395_CR62","doi-asserted-by":"crossref","unstructured":"Zhao H, Tian M, Sun S, Shao J, Yan J, Yi S, Wang X, Tang X (2017) Spindle net: person re-identification with human body region guided feature decomposition and fusion. In: IEEE conference on computer vision and pattern recognition, pp 1077\u20131085","DOI":"10.1109\/CVPR.2017.103"},{"key":"8395_CR63","doi-asserted-by":"crossref","unstructured":"Zhao L, Li X, Wang J, Zhuang Y (2017) Deeply-learned part-aligned representations for person re-identification. In: IEEE international conference on computer vision, pp 3219\u20133228","DOI":"10.1109\/ICCV.2017.349"},{"key":"8395_CR64","doi-asserted-by":"crossref","unstructured":"Zhao R, Ouyang W, Wang X (2013) Unsupervised salience learning for person re-identification. In: IEEE conference on computer vision and pattern recognition, pp 3586\u20133593","DOI":"10.1109\/CVPR.2013.460"},{"key":"8395_CR65","unstructured":"Zheng L, Huang Y, Lu H, Yang Y (2017) Pose invariant embedding for deep person re-identification. arXiv:1701.07732"},{"key":"8395_CR66","doi-asserted-by":"crossref","unstructured":"Zheng L, Shen L, Tian L, Wang S, Wang J, Tian Q (2016) Scalable person re-identification: a benchmark. In: IEEE international conference on computer vision, pp 1116\u20131124","DOI":"10.1109\/ICCV.2015.133"},{"key":"8395_CR67","unstructured":"Zheng L, Yang Y, Hauptmann AG (2016) Person re-identification: past, present and future. arXiv:1610.02984"},{"issue":"3","key":"8395_CR68","doi-asserted-by":"publisher","first-page":"653","DOI":"10.1109\/TPAMI.2012.138","volume":"35","author":"WS Zheng","year":"2013","unstructured":"Zheng WS, Gong S, Xiang T (2013) Reidentification by relative distance comparison. IEEE Trans Pattern Anal Mach Intell 35(3):653\u2013668","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"8395_CR69","doi-asserted-by":"crossref","unstructured":"Zheng Z, Zheng L, Yang Y (2017) A discriminatively learned cnn embedding for person re-identification. ACM Trans Multimed Comput Commun Appl 14(1)","DOI":"10.1145\/3159171"},{"key":"8395_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: IEEE conference on computer vision and pattern recognition, pp 3774\u20133782","DOI":"10.1109\/ICCV.2017.405"},{"key":"8395_CR71","doi-asserted-by":"crossref","unstructured":"Zhong W, Jiang L, Zhang T, Ji J, Xiong H (2018) A multi-part convolutional attention network for fine-grained image recognition. In: International conference on pattern recognition, pp 1857\u20131862","DOI":"10.1109\/ICPR.2018.8545225"},{"issue":"21","key":"8395_CR72","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1016\/j.neucom.2019.01.005","volume":"334","author":"W Zhong","year":"2019","unstructured":"Zhong W, Jiang L, Zhang T, Ji J, Xiong H (2019) Combining multilevel feature extraction and multi-loss learning for person re-identification. Neurocomputing 334(21):68\u201378","journal-title":"Neurocomputing"},{"key":"8395_CR73","doi-asserted-by":"crossref","unstructured":"Zhong W, Xiong H, Yang Z, Zhang T (2017) Bi-directional long short-term memory architecture for person re-identification with modified triplet embedding. In: IEEE international conference on image processing, pp 1562\u20131566","DOI":"10.1109\/ICIP.2017.8296544"},{"key":"8395_CR74","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1016\/j.jvcir.2019.06.001","volume":"62","author":"W Zhong","year":"2019","unstructured":"Zhong W, Zhang T, Jiang L, Ji J, Zhang Z, Xiong H (2019) Discriminative representation learning for person re-identification via multi-loss training. J Vis Commun Image Represent 62:267\u2013278","journal-title":"J Vis Commun Image Represent"},{"key":"8395_CR75","doi-asserted-by":"crossref","unstructured":"Zhong Z, Zheng L, Cao D, Li S (2017) Re-ranking person re-identification with k-reciprocal encoding. In: IEEE conference on computer vision and pattern recognition, pp 1318\u20131327","DOI":"10.1109\/CVPR.2017.389"},{"key":"8395_CR76","unstructured":"Zhong Z, Zheng L, Kang G, Li S, Yang Y (2017) Random erasing data augmentation. arXiv:1708.04896"},{"key":"8395_CR77","doi-asserted-by":"crossref","unstructured":"Zhong Z, Zheng L, Zheng Z, Li S, Yang Y (2018) Camera style adaptation for person re-identification. In: IEEE conference on computer vision and pattern recognition, pp 5157\u20135166","DOI":"10.1109\/CVPR.2018.00541"},{"key":"8395_CR78","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: IEEE international conference on computer vision, pp 2242\u20132251","DOI":"10.1109\/ICCV.2017.244"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-019-08395-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-019-08395-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-019-08395-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,5,24]],"date-time":"2021-05-24T23:45:20Z","timestamp":1621899920000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-019-08395-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,5,25]]},"references-count":78,"journal-issue":{"issue":"31-32","published-print":{"date-parts":[[2020,8]]}},"alternative-id":["8395"],"URL":"https:\/\/doi.org\/10.1007\/s11042-019-08395-2","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,5,25]]},"assertion":[{"value":"24 January 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 October 2019","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 October 2019","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 May 2020","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}