[1] 张耿宁, 王家宝, 张亚非, 等. 基于特征融合的行人重识别方法[J]. 计算机工程与应用,2017,53(12):185-189,240. (ZHANG G N,WANG J B,ZHANG Y F, et al. Person re-identification method based on feature fusion[J]. Computer Engineering and Applications,2017,53(12):185-189,240.) [2] 朱小波, 车进. 基于特征融合与子空间学习的行人重识别算法[J]. 激光与光电子学进展,2019,56(2):156-162. (ZHU X B, CHE J. Person re-identification algorithm based on feature fusion and subspace learning[J]. Laser and Optoelectronics Progress, 2019,56(2):156-162.) [3] 唐松. 基于显著特征的行人重识别方法研究[D]. 南京:南京邮电大学,2017. (TANG S. Person re-identification based on saliency[D]. Nanjing:Nanjing University of Posts and Telecommunications,2017.) [4] 陈兵, 查宇飞, 李运强, 等. 基于卷积神经网络判别特征学习的行人重识别[J]. 光学学报,2018,38(7):255-261.(CHEN B, ZHA Y F,LI Y Q,et al. Person re-identification based on convolutional neural network discriminative feature learning[J]. Acta Optica Sinica,2018,38(7):255-261.) [5] AHMED E,JONES M,MARKS T K. An improved deep learning architecture for person re-identification[C]//Proceedings of the 2015 IEEE Conference on Computer Vision and Pattern Recognition. Piscataway:IEEE,2015:3908-3916. [6] HE L,LIANG J,LI H,et al. Deep spatial feature reconstruction for partial person re-identification:alignment-free approach[C]//Proceedings of the 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Piscataway:IEEE,2018:7073-3082. [7] SUN Y,ZHENG L,YANG Y,et al. Beyond part models:person retrieval with refined part pooling[C]//Proceedings of the 2018 Proceedings of the European Conference on Computer Vision,LNCS 1120. Cham:Springer,2018:501-518. [8] LI W,ZHU X,GONG S. Harmonious attention network for person re-identification[C]//Proceedings of the 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Piscataway:IEEE,2018:2285-2294. [9] XU J,ZHAO R,ZHU F,et al. Attention-aware compositional network for person re-identification[C]//Proceedings of the 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Piscataway:IEEE,2018:2119-2128. [10] 陈首兵, 王洪元, 金翠, 等. 基于孪生网络和重排序的行人重识别[J]. 计算机应用,2018,38(11):3161-3166.(CHEN S B, WANG H Y,JIN C,et al. Person re-identification based on siamese network and reordering[J]. Journal of Computer Applications,2018,38(11):3161-3166.) [11] ZHENG L,SHEN L,TIAN L,et al. Scalable person re-identification:a benchmark[C]//Proceedings of the 2015 IEEE International Conference on Computer Vision. Piscataway:IEEE,2015:1116-1124. [12] ZHENG Z,ZHENG L,YANG Y. Unlabeled samples generated by GAN improve the person re-identification baseline in vitro[C]//Proceedings of the 2017 IEEE International Conference on Computer Vision. Piscataway:IEEE,2017:3774-3782. [13] LIAO S,HU Y,ZHU X,et al. Person re-identification by local maximal occurrence representation and metric learning[C]//Proceedings of the 2015 IEEE Conference on Computer Vision and Pattern Recognition. Piscataway:IEEE,2015:2197-2206. [14] WANG J,ZHU X,GONG S,et al. Transferable joint attributeidentity deep learning for unsupervised person re-identification[C]//Proceedings of the 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Piscataway:IEEE, 2018:2275-2284. [15] SUN Y,ZHENG L,DENG W,et al. SVDNet for pedestrian retrieval[C]//Proceedings of the 2017 IEEE International Conference on Computer Vision. Piscataway:IEEE,2017:3820-3828. [16] CHEN W,CHEN X,ZHANG J,et al. Beyond triplet loss:a deep quadruplet network for person re-identification[C]//Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition. Piscataway:IEEE,2017:1320-1329. [17] ZHONG Z,ZHENG L,ZHENG Z,et al. Camera style adaptation for person re-identification[C]//Proceedings of the 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Piscataway:IEEE,2018:5157-5166. [18] ZHONG Z,ZHENG L,CAO D,et al. Re-ranking person re-identification with k-reciprocal encoding[C]//Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition. Piscataway:IEEE,2017:3652-3661. |