[1] LIAO S C,HU Y,ZHU X Y,et al.Person re-identification by local maximal occurrence representation and metric learning[C]//2015 IEEE Conference on Computer Vision and Pattern Recognition.Piscataway:IEEE Press,2015:2197-2206. [2] DE MAESSCHALCK R,JOUAN-RIMBAUD D,MASSART D L.The Mahalanobis distance[J].Chemometrics and Intelligent Laboratory Systems,2000,50(1):1-18. [3] YI D,LEI Z,LIAO S C,et al.Deep metric learning for person re-identification[C]//2014 22nd International Conference on Pattern Recognition.Piscataway:IEEE Press,2014:34-39. [4] LI W,ZHAO R,XIAO T,et al.DeepReID:Deep filter pairing neural network for person re-identification[C]//2014 IEEE Conference on Computer Vision and Pattern Recognition.Piscataway:IEEE Press,2014:152-159. [5] VARIOR R R,SHUAI B,LU J,et al.A Siamese long short-term memory architecture for human re-identification[C]//European Conference on Computer Vision.Berlin:Springer,2016:135-153. [6] ZHANG X,LUO H,FAN X,et al.AlignedReID:Surpassing human-level performance in person re-identification[EB/OL].(2018-01-31)[2020-03-02].https://arxiv.org/abs/1711.08184. [7] DENG W,ZHENG L,YE Q,et al.Image-image domain adaptation with preserved self-similarity and domain-dissimilarity for person re-identification[C]//2018 IEEE Conference on Computer Vision and Pattern Recognition.Piscataway:IEEE Press,2018:994-1003. [8] LUO H,JIANG W,ZHANG X,et al.AlignedReID++:Dynamically matching local information for person re-identification[J].Pattern Recognition,2019,94:53-61. [9] HERMANS A,BEYER L,LEIBE B.In defense of the triplet loss for person re-identification[EB/OL].(2017-11-21)[2020-03-02].https://arxiv.org/abs/1703.07737. [10] IOFFE S,SZEGEDY C.Batch normalization:Accelerating deep network training by reducing internal covariate shift[EB/OL].(2015-03-02)[2020-03-02].https://arxiv.org/abs/1502.03167. [11] LI X,HU X,YANG J.Spatial group-wise enhance:Improving semantic feature learning in convolutional networks[EB/OL].(2019-05-25)[2020-03-02].https://arxiv.org/abs/1905.09646. [12] PAN X,LUO P,SHI J,et al.Two at once:Enhancing learning and generalization capacities via IBN-Net[EB/OL].(2018-07-27)[2020-03-02].https://arxiv.org/abs/1807.09441. [13] XIAO Q,LUO H,ZHANG C.Margin sample mining loss:A deep learning based method for person re-identification[EB/OL].(2017-10-07)[2020-03-02].https://arxiv.org/abs/1710.00478. [14] ZHENG L,YANG Y,HAUPTMANN A G.Person re-identification:Past,present and future[EB/OL].(2016-10-10)[2020-03-02].https://arxiv.org/abs/1610.02984. [15] LIU H,FENG J S,QI M B,et al.End-to-end comparative attention networks for person re-identification[J].IEEE Transactions on Image Processing,2017,26(7):3492-3506. [16] CHENG D,GONG Y H,ZHOU S P,et al.Person re-identification by multi-channel parts-based CNN with improved triplet loss function[C]//2016 IEEE Conference on Computer Vision and Pattern Recognition.Piscataway:IEEE Press,2016:1335-1344. [17] 杜鹏,宋永红,张鑫瑶.基于自注意力模态融合网络的跨模态行人再识别方法研究[J/OL].自动化学报:1-12(2019-10-16)[2020-01-06].https://kns.cnki.net/kcms/detail/detail.aspx?doi=10.16383/j.aas.c190340.DU P,SONG Y H,ZHANG X Y.Self-attention cross-modality fusion network for cross-modality person re-identification[J/OL].Acta Automatica Sinica:1-12(2019-10-16)[2020-01-06].https://kns.cnki.net/kcms/detail/detail.aspx?doi=10.16383/j.aas.c190340(in Chinese). [18] 张丽红,孙志琳.基于多层深度特征融合的行人再识别研究[J].测试技术学报,2018,32(4):48-52.ZHANG L H,SUN Z L.Person re-identification based on multi-layer deep feature fusion[J].Journal of Test and Measurement Technology,2018,32(4):48-52(in Chinese). [19] 李鹏,王德勇,师文喜,等.大数据环境下基于深度学习的行人再识别[J].北京邮电大学学报,2019,42(6):29-34.LI P,WANG D Y,SHI W X,et al.Research on person re-identification based on deep learning under big data environment[J].Journal of Beijing University of Posts and Telecommunications,2019,42(6):29-34(in Chinese). [20] SUN Y,ZHENG L,DENG W,et al.SVDNet for pedestrian retrieval[C]//2017 IEEE International Conference on Computer Vision (ICCV).Piscataway:IEEE Press,2017:3820-3828. [21] SARFRAZ M S,SCHUMANN A,EBERLE A,et al.A pose-sensitive embedding for person re-identification with expanded cross neighborhood re-ranking[EB/OL].(2018-04-05)[2020-03-02].https://arxiv.org/abs/1711.10378. [22] AN L,QIN Z,CHEN X J,et al.Multi-level common space learning for person re-identification[J].IEEE Transactions on Circuits & Systems for Video Technology,2018,28(8):1777-1787. [23] LI W,ZHU X,GONG S.Harmonious attention network for person re-identification[C]//2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.Piscataway:IEEE Press,2018:2285-2294. |