[1] Guo H,Zhao C,Liu Z,et al.Learning coarse-to-fine structured feature embedding for vehicle re-identification[A].32th AAAI Conference on Artificial Intelligence[C].New Orleans,Louisiana,USA:AAAI,2018.6853-6860.
[2] Shen Y,Xiao T,Li H,et al.Learning deep neural networks for vehicle Re-ID with visual-spatio-temporal path proposals[A].2017 IEEE International Conference on Computer Vision[C].Venice,Italy:ICCV,2017.1900-1909.
[3] Zapletal D,Herout A.Vehicle re-identification for automatic video traffic surveillance[A].Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition[C].Las Vegas,Nevada,USA:IEEE,2016.25-31.
[4] Liu X,Liu W,Ma H,et al.Large-scale vehicle re-identification in urban surveillance videos[A].IEEE International Conference on Multimedia and Expo[C].Seattle,WA,USA:IEEE,2016.1-6.
[5] Liu H,Tian Y,Wang Y,et al.Deep relative distance learning:tell the difference between similar vehicles[A].Computer Vision and Pattern Recognition[C].Las Vegas,Nevada,USA:IEEE,2016.2167-2175.
[6] Zhou Y,Shao L.Viewpoint-aware attentive multi-view inference for vehicle re-identification:computer vision and pattern recognition[A].Computer Vision and Pattern Recognition[C].Salt Lake City,UT,USA:IEEE,2018.6489-6498.
[7] Wang Z,Wang X,Tang L,et al.Orientation invariant feature embedding and spatial temporal regularization for vehicle re-identification[A].2017 IEEE International Conference on Computer Vision[C].Venice,Italy:IEEE,2017.379-387.
[8] Xiao T,Li H,Ouyang W,et al.Learning deep feature representations with domain guided dropout for person re-identification[A].IEEE Conference on Computer Vision and Pattern Recognition[C].Las Vegas,Nevada,USA:IEEE,2016.1249-1258.
[9] Liao S,Hu Y,Zhu X,et al.Person re-identification by local maximal occurrence representation and metric learning[A].IEEE Conference on Computer Vision and Pattern Recognition[C].Boston,Massachusetts,USA:IEEE,2015.2197-2206.
[10] Wu C W,Liu C T,Chiang C E,et al.Vehicle re-identification with the space-time prior[A].In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops[C].Salt Lake City,UT,USA:IEEE,2018.121-128.
[11] Chen G,Lu J,Yang M,et al.Spatial-temporal attention-aware learning for video-based person re-identification[J].IEEE Transactions on Image Processing,2019,28(9):4192-4205.
[12] He B,Li J,Zhao Y,et al.Part-regularized near-duplicate vehicle re-identification[A].Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition[C].Long Beach,CA,USA:IEEE,2019.3997-4005.
[13] Liu X,Zhang S,Huang Q,et al.Ram:a region-aware deep model for vehicle re-identification[A].2018 IEEE International Conference on Multimedia and Expo (ICME)[C].San Diego,USA:IEEE,2018.1-6.
[14] Hermans A,Beyer L,Leibe B.In Defense of the Triplet Loss for Person Re-identification[EB/OL].https://arxiv.org/abs/1703.07737,2017.
[15] Yadav J,Sharma M.A review of K-mean algorithm[J].International journal of engineering trends and technology,2013,4(7):2972-2976.
[16] He K,Zhang X,Ren S,Sun J.Deep residual learning for image recognition[A].Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition[C].Las Vegas,Nevada,USA:IEEE,2016.770-778.
[17] Liu X,Liu W,Mei T,Ma H.A deep learning-based approach to progressive vehicle re-identification for urbansurveillance[A].ECCV 2016[C].Amsterdam,Netherlands:Springer, 2016.869-884. |