{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T01:23:46Z","timestamp":1770341026457,"version":"3.49.0"},"reference-count":66,"publisher":"Springer Science and Business Media LLC","issue":"12","license":[{"start":{"date-parts":[[2021,2,10]],"date-time":"2021-02-10T00:00:00Z","timestamp":1612915200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,2,10]],"date-time":"2021-02-10T00:00:00Z","timestamp":1612915200000},"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":["61876056"],"award-info":[{"award-number":["61876056"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61771180"],"award-info":[{"award-number":["61771180"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2021,5]]},"DOI":"10.1007\/s11042-020-10431-5","type":"journal-article","created":{"date-parts":[[2021,2,10]],"date-time":"2021-02-10T07:51:10Z","timestamp":1612943470000},"page":"17645-17666","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Mask-guided dual attention-aware network for visible-infrared person re-identification"],"prefix":"10.1007","volume":"80","author":[{"given":"Meibin","family":"Qi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4668-0836","authenticated-orcid":false,"given":"Suzhi","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guanghong","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianguo","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingjing","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cuiqun","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,2,10]]},"reference":[{"key":"10431_CR1","unstructured":"Bahdanau D, Cho K, Bengio Y (2015) Neural machine translation by jointly learning to align and translate. In: PICLR"},{"key":"10431_CR2","doi-asserted-by":"crossref","unstructured":"Barra P, Bisogni C, Nappi M, Freire-Obreg\u00f3n D, Castrill\u00f3n-Santana M (2020) Gotcha-i: a multiview human videos dataset. security in computing and communications","DOI":"10.1007\/978-981-15-4825-3_17"},{"key":"10431_CR3","doi-asserted-by":"crossref","unstructured":"Bedagkar-Gala A, Shah S (2014) A survey of approaches and trends in person re-identification. In: Image Vision Comput, pp 270\u2013286","DOI":"10.1016\/j.imavis.2014.02.001"},{"key":"10431_CR4","doi-asserted-by":"crossref","unstructured":"Chen T, Ding S, Xie J, Yuan Y, Chen W, Yang Y, Wang Z (2019) ABD-Net:, Attentive but Diverse Person Re-Identification. arXiv:1908.01114","DOI":"10.1109\/ICCV.2019.00844"},{"key":"10431_CR5","doi-asserted-by":"crossref","unstructured":"Chen D, Zhang S, Ouyang W, Yang J, Tai Y (2018) Person search via a mask-guided two-stream cnn model. arXiv:1807.08107","DOI":"10.1007\/978-3-030-01234-2_45"},{"key":"10431_CR6","doi-asserted-by":"crossref","unstructured":"Chen L, Zhang H, Xiao J, Nie L, Shao J, Liu W, Chu T (2017) SCA-CNN : Spatial And channel-wise attention in convolutional networks for image captioning. In: CVPR","DOI":"10.1109\/CVPR.2017.667"},{"key":"10431_CR7","doi-asserted-by":"crossref","unstructured":"Cheng D, Li X, Qi M, Liu X, Chen C, Niu D (2019) Exploring cross-modality commonalities via dual-stream multi-branch network for infrared-visible person re-identification. In: IEEE Access, pp 12824\u201312834","DOI":"10.1109\/ACCESS.2020.2966002"},{"key":"10431_CR8","doi-asserted-by":"crossref","unstructured":"Choi S, Lee S, Kim Y, Kim T, Kim C (2020) Hi-cmd: hierarchical cross-modality disentanglement for visible-infrared person re-identification. In: CVPR","DOI":"10.1109\/CVPR42600.2020.01027"},{"key":"10431_CR9","doi-asserted-by":"crossref","unstructured":"Dai P, Ji R, Wang H, Wu Q, Huang Y (2018) Crossmodality person re-identification with generative adversarial training. In: IJCAI, pp 677\u2013683","DOI":"10.24963\/ijcai.2018\/94"},{"key":"10431_CR10","unstructured":"Dalal N, Triggs B (2005) Histograms of oriented gradients for human detection. In: CVPR"},{"key":"10431_CR11","unstructured":"De Marsico M, Distasi R, Ricciardi S, Riccio D (2014) A comparison of approaches for person re-identification. In: ICPRAM, pp 189\u2013198"},{"key":"10431_CR12","doi-asserted-by":"crossref","unstructured":"Feng Z, Lai J, Xie X (2019) Learning modality-specific representations for visible-infrared person re-identification, IEEE Transactions on Image Processing, 29, 579\u2013590","DOI":"10.1109\/TIP.2019.2928126"},{"key":"10431_CR13","doi-asserted-by":"crossref","unstructured":"Fu Y, Wei Y, Zhou Y, Shi H, Huang G, Wang X, Yao Z, Huang T (2018) Horizontal pyramid matching for person reidentification. arXiv:1804.05275","DOI":"10.1609\/aaai.v33i01.33018295"},{"key":"10431_CR14","doi-asserted-by":"crossref","unstructured":"Guler RA, Trigeorgis G, Antonakos E, Snape P, Zafeiriou S, Kokkino I (2016) Densereg: Fully convolutional dense shape regression in-the-wild. arXiv:1612.01202","DOI":"10.1109\/CVPR.2017.280"},{"key":"10431_CR15","doi-asserted-by":"crossref","unstructured":"Hao Y, Li J, Wang N, Gao X (2020) Modality adversarial neural network for visible-thermal person re-identification, p Pattern Recognition","DOI":"10.1016\/j.patcog.2020.107533"},{"key":"10431_CR16","doi-asserted-by":"crossref","unstructured":"Hao Y, Wang N, Li J, Gao X (2019) Hsme: Hypersphere manifold embedding for visible thermal person re-identification. In: AAAI, pp 8385\u20138392","DOI":"10.1609\/aaai.v33i01.33018385"},{"key":"10431_CR17","doi-asserted-by":"crossref","unstructured":"He K, Gkioxari G, Dollar P, Girshick R (2017) Mask r-cnn. arXiv:1703.06870","DOI":"10.1109\/ICCV.2017.322"},{"key":"10431_CR18","unstructured":"Hermans A, Beyer L, Leibe B (2017) In defense of the triplet loss for person re-identification. arXiv:1703.07737"},{"key":"10431_CR19","doi-asserted-by":"crossref","unstructured":"Hu J, Shen L, Sun G (2017) Squeeze-and-excitation networks. arXiv:1709.01507","DOI":"10.1109\/CVPR.2018.00745"},{"key":"10431_CR20","unstructured":"Jaderberg M, Simonyan K, Zisserman A, Kavukcuoglu K (2015) Spatial transformer networks. In: NIPS"},{"key":"10431_CR21","doi-asserted-by":"crossref","unstructured":"Jiang J, Jin K, Qi M, Wang Q, Wu J, Chen C (2020) A cross-modal multi-granularity attention network for rgb-ir person re-identification. In: Neurocomputing","DOI":"10.1016\/j.neucom.2020.03.109"},{"key":"10431_CR22","doi-asserted-by":"crossref","unstructured":"Kalayeh MM, Basaran E, Gokmen M, Kamasak ME, Shah M (2018) Human semantic parsing for person re-identification. In: CVPR, pp 1062\u20131071","DOI":"10.1109\/CVPR.2018.00117"},{"key":"10431_CR23","doi-asserted-by":"crossref","unstructured":"Kang JK, Hoang TM, Park KR (2019) Person re-identification between visible and thermal camera images based on deep residual CNN using single input. [J]. IEEE Access, 7: pp 57972\u201357984.","DOI":"10.1109\/ACCESS.2019.2914670"},{"key":"10431_CR24","doi-asserted-by":"crossref","unstructured":"Kumar V, Namboodiri A, Paluri M, Jawahar C (2017) Pose-aware person recognition. In: CVPR","DOI":"10.1109\/CVPR.2017.719"},{"key":"10431_CR25","doi-asserted-by":"crossref","unstructured":"Lan X, Wang H, Gong S, Zhu X (2017) Deep reinforcement learning attention selection for person re-identification. In: BMVC","DOI":"10.5244\/C.31.121"},{"key":"10431_CR26","doi-asserted-by":"crossref","unstructured":"Li S, Bak S, Car P, Wang X (2018) Diversity regularized spatiotemporal attention for video-based person re-identificatio. In: CVPR","DOI":"10.1109\/CVPR.2018.00046"},{"key":"10431_CR27","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: CVPR","DOI":"10.1109\/CVPR.2017.782"},{"key":"10431_CR28","doi-asserted-by":"crossref","unstructured":"Li Y, Qi H, Dai J, Ji X, Wei Y (2017) Fully convolutional instance-aware semantic segmentation. In: CVPR","DOI":"10.1109\/CVPR.2017.472"},{"key":"10431_CR29","doi-asserted-by":"crossref","unstructured":"Li W, Zhu X, Gong S (2018) Harmonious attention network for person re-identification. In: CVPR","DOI":"10.1109\/CVPR.2018.00243"},{"key":"10431_CR30","unstructured":"Liang X, Gong K, Shen X, Lin L (2018) Look into person: Joint body parsing & pose estimation network and a new benchmark. arXiv:1804.01984"},{"key":"10431_CR31","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: CVPR, pp 2197\u20132206","DOI":"10.1109\/CVPR.2015.7298832"},{"key":"10431_CR32","doi-asserted-by":"crossref","unstructured":"Lin TY, Maire M, Belongie S, Hays J, Perona P, Ramanan D, Dollar P, Zitnick CL (2014) Microsoft COCo: common objects in context. In: ECCV","DOI":"10.1007\/978-3-319-10602-1_48"},{"key":"10431_CR33","doi-asserted-by":"crossref","unstructured":"Lin D, Tang X (2006) Inter-modality face recognition. In: ECCV","DOI":"10.1007\/11744085_2"},{"key":"10431_CR34","doi-asserted-by":"crossref","unstructured":"Lin L, Wang G, Zuo W, Feng X, Zhang L (2017) Cross-domain visual matching via generalized similarity measure and feature learning. In: TPAMI, pp 1089\u20131102","DOI":"10.1109\/TPAMI.2016.2567386"},{"key":"10431_CR35","doi-asserted-by":"crossref","unstructured":"Liu X, Zhao H, Tian M, Sheng L, Shao J, Yi S, Yan J, Wang X (2017) Hydraplus-net: Attentive deep features for pedestrian analysis. In: ICCV","DOI":"10.1109\/ICCV.2017.46"},{"key":"10431_CR36","doi-asserted-by":"crossref","unstructured":"Nguyen DT, Hong HG, Kim KW, Park KR (2017) Person recognition system based on a combination of body images from visible light and thermal cameras. Sensors","DOI":"10.3390\/s17030605"},{"key":"10431_CR37","doi-asserted-by":"crossref","unstructured":"Russakovsky O, Deng J, Su H, Krause J, Satheesh S, Ma S, Huang Z, Karpathy A, Khosla A, Bernstein M, Berg AC, Fei-Fei L (2015) ImageNet large scale visual recognition challenge. In: IJCV","DOI":"10.1007\/s11263-015-0816-y"},{"key":"10431_CR38","doi-asserted-by":"crossref","unstructured":"Si C, Chen W, Wang W, Wang L, Tan T (2019) An attention enhanced graph convolutional lstm network for skeleton-based action recognition. In: CVPR, pp 1227\u20131236","DOI":"10.1109\/CVPR.2019.00132"},{"key":"10431_CR39","doi-asserted-by":"crossref","unstructured":"Song C, Huang Y, Ouyang W, Wang L (2018) Mask-guided contrastive attention model for person re-identification. In: CVPR","DOI":"10.1109\/CVPR.2018.00129"},{"key":"10431_CR40","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: ICCV","DOI":"10.1109\/ICCV.2017.427"},{"key":"10431_CR41","doi-asserted-by":"crossref","unstructured":"Sun Y, Xu Q, Li Y, Zhang C, Li Y, Wang S, Sun J (2019) Perceive where to focus: Learning visibility-aware part-level features for partial person re-identification. In: CVPR","DOI":"10.1109\/CVPR.2019.00048"},{"key":"10431_CR42","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: ECCV, pp 501\u2013518","DOI":"10.1007\/978-3-030-01225-0_30"},{"key":"10431_CR43","doi-asserted-by":"crossref","unstructured":"Szegedy C, Vanhoucke V, Ioffe S, Shlens J, Wojna Z (2016) Rethinking the inception architecture for computer vision. In: CVPR","DOI":"10.1109\/CVPR.2016.308"},{"key":"10431_CR44","doi-asserted-by":"crossref","unstructured":"Tran D, Bourdev L, Fergus R, Torresani L, Paluri M (2015) Learning spatiotemporal features with 3d convolutional networks. In: ICCV","DOI":"10.1109\/ICCV.2015.510"},{"key":"10431_CR45","doi-asserted-by":"crossref","unstructured":"Vezzani R, Baltieri D, Cucchiara R (2013) People Reidentification in surveillance and forensics: a survey. In: ACM computing surveys","DOI":"10.1145\/2543581.2543596"},{"key":"10431_CR46","doi-asserted-by":"crossref","unstructured":"Wang X, Girshick RB, Gupta A, He K (2018) Non-local neural networks. In: CVPR","DOI":"10.1109\/CVPR.2018.00813"},{"key":"10431_CR47","doi-asserted-by":"crossref","unstructured":"Wang Y, Wang L, You Y, Zou X, Chen V, Li S, Huang G, Hariharan B, et al., Weinberger KQ (2018) Resource aware person re-identification across multiple resolutions. In: CVPR, pp 8042\u20138051","DOI":"10.1109\/CVPR.2018.00839"},{"key":"10431_CR48","doi-asserted-by":"crossref","unstructured":"Wang G, Yuan Y, Chen X, Li J, Zhou X (2018) Learning discriminative features with multiple granularities for person reidentification. arXiv:1804.01438","DOI":"10.1145\/3240508.3240552"},{"key":"10431_CR49","doi-asserted-by":"crossref","unstructured":"Wang Z, Zheng Y, Chuang Y-Y, Satoh S (2019) Learning to reduce dual-level discrepancy for infraredvisible person re-identification. In: CVPR","DOI":"10.1109\/CVPR.2019.00071"},{"key":"10431_CR50","doi-asserted-by":"crossref","unstructured":"Wu J, Liu H, Jiang J, Qi M, Ren B, Li X, Wang Y (2020) Person attribute recognition by sequence contextual relation learning. In: IEEE","DOI":"10.1109\/TCSVT.2020.2982962"},{"key":"10431_CR51","doi-asserted-by":"crossref","unstructured":"Wu A, Zheng W-S, Yu H-X, Gong S, Lai J (2017) Rgb-infrared cross-modality person re-identification. In: ICCV, pp 5380\u20135389","DOI":"10.1109\/ICCV.2017.575"},{"key":"10431_CR52","unstructured":"Xu K, Ba J, Kiros R, Cho K, Courville A, Salakhutdinov R, Zemel R, Bengio Y (2015) Show, attend and tell: Neural image caption generation with visual attention. In: ICML"},{"key":"10431_CR53","doi-asserted-by":"crossref","unstructured":"Xu S, Cheng Y, Gu K, Yang Y, Chang S, Zhou P (2017) Jointly attentive spatial-temporal pooling networks for video-based person reidentification. In: IEEE, pp 4733\u20134742","DOI":"10.1109\/ICCV.2017.507"},{"key":"10431_CR54","doi-asserted-by":"crossref","unstructured":"Yang F, Yan K, Lu S, Jia H, Xie X, Gao W (2019) Attention driven person re-identification. In: Pattern Recognit, pp 143\u2013155","DOI":"10.1016\/j.patcog.2018.08.015"},{"key":"10431_CR55","doi-asserted-by":"crossref","unstructured":"Ye M, Lan X, Li J, Yuen PC (2018) Hierarchical discriminative learning for visible thermal person re-identification. In: AAAI","DOI":"10.1145\/3343031.3351043"},{"key":"10431_CR56","doi-asserted-by":"crossref","unstructured":"Ye M, Lan X, Wang Z, Yuen PC (2019) Bi-directional Center-Constrained Top-Ranking for Visible Thermal Person Re-Identification. In: IEEE TIFS","DOI":"10.1109\/TIFS.2019.2921454"},{"key":"10431_CR57","doi-asserted-by":"crossref","unstructured":"Ye M, Wang Z, Lan X, Yuen PC (2018) Visible thermal person re-identification via dual-constrained topranking. In: IJCAI","DOI":"10.24963\/ijcai.2018\/152"},{"key":"10431_CR58","unstructured":"Zagoruyko S, Komodakis N (2016) Paying more attention to attention: Improving the performance of convolutional neural networks via attention transfer. arXiv:1612.03928"},{"key":"10431_CR59","doi-asserted-by":"crossref","unstructured":"Zhang Y, Guo J, Huang Z, Qiu W, Fan H (2019) Multi-layer attention for person re-identification. In: MATEC web of conferences, Vol. 277","DOI":"10.1051\/matecconf\/201927702025"},{"key":"10431_CR60","unstructured":"Zhang X, Luo H, Fan X, Xiang W, Sun Y, Xiao Q, Jiang W, Zhang C, Sun J (2017) Alignedreid: Surpassing human-level performance in person re-identification. arXiv:1711.08184"},{"key":"10431_CR61","doi-asserted-by":"crossref","unstructured":"Zhao L, Li X, Zhuang Y, JingdongWang (2017) Deeply-learned part-aligned representations for person re-identification. In: ICCV","DOI":"10.1109\/ICCV.2017.349"},{"key":"10431_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: CVPR","DOI":"10.1109\/CVPR.2017.103"},{"key":"10431_CR63","unstructured":"Zheng L, Huang Y, Lu H, Yang Y (2017) Pose invariant embedding for deep person re-identification. arXiv:1701.07732"},{"key":"10431_CR64","doi-asserted-by":"crossref","unstructured":"Zheng M, Karanam S, Wu Z, Radke RJ (2019) Re-identification with consistent attentive siamese networks. In: CVPR","DOI":"10.1109\/CVPR.2019.00588"},{"key":"10431_CR65","unstructured":"Zheng L, Yang Y, Hauptmann AG (2016) Person re-identification: Past, present and future. arXiv:1610.02984"},{"key":"10431_CR66","doi-asserted-by":"crossref","unstructured":"Zhou B, Khosla A, Lapedriza A, Oliva A, Torralba A (2016) Learning deep features for discriminative localization. In: CVPR, pp 2921\u20132929","DOI":"10.1109\/CVPR.2016.319"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-020-10431-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-020-10431-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-020-10431-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,5,20]],"date-time":"2021-05-20T08:56:42Z","timestamp":1621501002000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-020-10431-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,2,10]]},"references-count":66,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2021,5]]}},"alternative-id":["10431"],"URL":"https:\/\/doi.org\/10.1007\/s11042-020-10431-5","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,2,10]]},"assertion":[{"value":"10 January 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 August 2020","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 December 2020","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 February 2021","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}