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This study explores a simple but strong baseline for person re-identification (ReID).
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei, “Imagenet: A large-scale hierarchical image database,” in 2009 IEEE conference on computer vision and pattern recognition . Ieee, 2009, pp. 248–255
2009
Earlier work this paper cites.
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio, “Generative adversarial nets,” in Advances in neural information processing systems , 2014, pp. 2672–2680
2014
Earlier work this paper cites.
C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich, “Going deeper with convolutions,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2015, pp. 1–9
2015
Earlier work this paper cites.
F. Schroff, D. Kalenichenko, and J. Philbin, “Facenet: A unified embedding for face recognition and clustering,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2015, pp. 815–823
2015
Earlier work this paper cites.
S. Ioffe and C. Szegedy, “Batch normalization: Accelerating deep network training by reducing internal covariate shift,” in International Conference on Machine Learning , 2015, pp. 448–456
2015
Earlier work this paper cites.
K. He, X. Zhang, S. Ren, and J. Sun, “Delving deep into rectifiers: Surpassing human-level performance on imagenet classification,” in Proceedings of the IEEE international conference on computer vision , 2015, pp. 1026–1034
2015
Earlier work this paper cites.
L. Zheng, L. Shen, L. Tian, S. Wang, J. Wang, and Q. Tian, “Scalable person re-identification: A benchmark,” in Computer Vision, IEEE International Conference , 2015
2015
Earlier work this paper cites.
K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2016, pp. 770–778
2016
Earlier work this paper cites.
M. Ye, C. Liang, Y. Yu, Z. Wang, Q. Leng, C. Xiao, J. Chen, and R. Hu, “Person reidentification via ranking aggregation of similarity pulling and dissimilarity pushing,” IEEE Transactions on Multimedia , vol. 18, no. 12, pp. 2553–2566, 2016
2016
Earlier work this paper cites.
C. Szegedy, V. Vanhoucke, S. Ioffe, J. Shlens, and Z. Wojna, “Rethinking the inception architecture for computer vision,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2016, pp. 2818–2826
2016
Earlier work this paper cites.
Y. Wen, K. Zhang, Z. Li, and Y. Qiao, “A discriminative feature learning approach for deep face recognition,” in European conference on computer vision . Springer, 2016, pp. 499–515
2016
Earlier work this paper cites.
E. Ristani, F. Solera, R. Zou, R. Cucchiara, and C. Tomasi, “Performance measures and a data set for multi-target, multi-camera tracking,” in European Conference on Computer Vision workshop on Benchmarking Multi-Target Tracking , 2016
2016
Earlier work this paper cites.
G. Huang, Z. Liu, L. Van Der Maaten, and K. Q. Weinberger, “Densely connected convolutional networks,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2017, pp. 4700–4708
2017
Earlier work this paper cites.
H. Liu, J. Feng, M. Qi, J. Jiang, and S. Yan, “End-to-end comparative attention networks for person re-identification,” IEEE Transactions on Image Processing , vol. 26, no. 7, pp. 3492–3506, 2017
2017
Earlier work this paper cites.
H. Zhao, M. Tian, S. Sun, J. Shao, J. Yan, S. Yi, X. Wang, and X. Tang, “Spindle net: Person re-identification with human body region guided feature decomposition and fusion,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2017, pp. 1077–1085
2017
Earlier work this paper cites.
L. Wei, S. Zhang, H. Yao, W. Gao, and Q. Tian, “Glad: Global-local-alignment descriptor for pedestrian retrieval,” in Proceedings of the 25th ACM international conference on Multimedia . ACM, 2017, pp. 420–428
2017
Earlier work this paper cites.
Z. Zheng, L. Zheng, and Y. Yang, “Unlabeled samples generated by gan improve the person re-identification baseline in vitro,” in Proceedings of the IEEE International Conference on Computer Vision , 2017, pp. 3754–3762
2017
Earlier work this paper cites.
Z. Zhong, L. Zheng, D. Cao, and S. Li, “Re-ranking person re-identification with k-reciprocal encoding,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2017, pp. 1318–1327
2017
Earlier work this paper cites.
2017
Cited alongside, same era.
X. Zhang, Z. Fang, Y. Wen, Z. Li, and Y. Qiao, “Range loss for deep face recognition with long-tailed training data,” in Proceedings of the IEEE International Conference on Computer Vision , 2017, pp. 5409–5418
2017
Cited alongside, same era.
2017
Cited alongside, same era.
Y. Sun, L. Zheng, W. Deng, and S. Wang, “Svdnet for pedestrian retrieval,” in Proceedings of the IEEE International Conference on Computer Vision , 2017, pp. 3800–3808
2017
Cited alongside, same era.
L. Wei, S. Zhang, W. Gao, and Q. Tian, “Person transfer gan to bridge domain gap for person re-identification,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2018, pp. 79–88
2018
Later among the works it cites.
X. Qian, Y. Fu, T. Xiang, W. Wang, J. Qiu, Y. Wu, Y.-G. Jiang, and X. Xue, “Pose-normalized image generation for person re-identification,” in Proceedings of the European Conference on Computer Vision (ECCV) , 2018, pp. 650–667
2018
Later among the works it cites.
Y. Zhao, Z. Jin, G.-j. Qi, H. Lu, and X.-s. Hua, “An adversarial approach to hard triplet generation,” in Proceedings of the European Conference on Computer Vision (ECCV) , 2018, pp. 501–517
2018
Later among the works it cites.
Y. Shen, H. Li, T. Xiao, S. Yi, D. Chen, and X. Wang, “Deep group-shuffling random walk for person re-identification,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2018, pp. 2265–2274
2018
Later among the works it cites.
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C. Wang, Q. Zhang, C. Huang, W. Liu, and X. Wang, “Mancs: A multi-task attentional network with curriculum sampling for person re-identification,” in Proceedings of the European Conference on Computer Vision (ECCV) , 2018, pp. 365–381
2018
Cited alongside, same era.
Y. Sun, L. Zheng, Y. Yang, Q. Tian, and S. Wang, “Beyond part models: Person retrieval with refined part pooling (and a strong convolutional baseline),” in Proceedings of the European Conference on Computer Vision (ECCV) , 2018, pp. 480–496
2018
Cited alongside, same era.
M. Jian, Q. Qi, J. Dong, Y. Yin, and K.-M. Lam, “Integrating qdwd with pattern distinctness and local contrast for underwater saliency detection,” Journal of visual communication and image representation , vol. 53, pp. 31–41, 2018
2018
Cited alongside, same era.
Z. Zheng, L. Zheng, and Y. Yang, “A discriminatively learned cnn embedding for person reidentification,” ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) , vol. 14, no. 1, p. 13, 2018
2018
Cited alongside, same era.
G. Wang, Y. Yuan, X. Chen, J. Li, and X. Zhou, “Learning discriminative features with multiple granularities for person re-identification,” in 2018 ACM Multimedia Conference on Multimedia Conference . ACM, 2018, pp. 274–282
2018
Cited alongside, same era.
X. Fan, H. Luo, X. Zhang, L. He, C. Zhang, and W. Jiang, “Scpnet: Spatial-channel parallelism network for joint holistic and partial person re-identification,” in Asian Conference on Computer Vision . Springer, 2018, pp. 19–34
2018
Cited alongside, same era.
M. Saquib Sarfraz, A. Schumann, A. Eberle, and R. Stiefelhagen, “A pose-sensitive embedding for person re-identification with expanded cross neighborhood re-ranking,” in The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , June 2018
2018
Cited alongside, same era.
C. Song, Y. Huang, W. Ouyang, and L. Wang, “Mask-guided contrastive attention model for person re-identification,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2018, pp. 1179–1188
2018
Cited alongside, same era.
E. Ristani and C. Tomasi, “Features for multi-target multi-camera tracking and re-identification,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2018, pp. 6036–6046
2018
Later among the works it cites.
2018
Later among the works it cites.
2018
Later among the works it cites.
H. Luo, Y. Gu, X. Liao, S. Lai, and W. Jiang, “Bag of tricks and a strong baseline for deep person re-identification,” in The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops , June 2019
2019
Closest in time.
Z. Wang, J. Jiang, Y. Yu, and S. Satoh, “Incremental re-identification by cross-direction and cross-ranking adaption,” IEEE Transactions on Multimedia , 2019
2019
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H. Luo, W. Jiang, X. Zhang, X. Fan, J. Qian, and C. Zhang, “Alignedreid++: Dynamically matching local information for person re-identification,” Pattern Recognition , vol. 94, pp. 53–61, 2019
2019
Closest in time.
M. Jian, Q. Qi, H. Yu, J. Dong, C. Cui, X. Nie, H. Zhang, Y. Yin, and K.-M. Lam, “The extended marine underwater environment database and baseline evaluations,” Applied Soft Computing , vol. 80, pp. 425–437, 2019
2019
Closest in time.
F. Xiong, Y. Xiao, Z. Cao, K. Gong, Z. Fang, and J. T. Zhou, “Good practices on building effective cnn baseline model for person re-identification,” in Tenth International Conference on Graphics and Image Processing (ICGIP 2018) , vol. 11069. International Society for Optics and Photonics, 2019, p. 110690I
2019
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L. Zheng, Y. Huang, H. Lu, and Y. Yang, “Pose invariant embedding for deep person re-identification,” IEEE Transactions on Image Processing , 2019
2019
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Z. Zhong, L. Zheng, Z. Zheng, S. Li, and Y. Yang, “Camstyle: A novel data augmentation method for person re-identification,” IEEE Transactions on Image Processing , vol. 28, no. 3, pp. 1176–1190, 2019
2019
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Z. Zheng, X. Yang, Z. Yu, L. Zheng, Y. Yang, and J. Kautz, “Joint discriminative and generative learning for person re-identification,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2019, pp. 2138–2147
2019
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S. Bai, P. Tang, P. H. Torr, and L. J. Latecki, “Re-ranking via metric fusion for object retrieval and person re-identification,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2019, pp. 740–749
2019
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X. Fan, W. Jiang, H. Luo, and M. Fei, “Spherereid: Deep hypersphere manifold embedding for person re-identification,” Journal of Visual Communication and Image Representation , 2019
2019
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F. Zheng, C. Deng, X. Sun, X. Jiang, X. Guo, Z. Yu, F. Huang, and R. Ji, “Pyramidal person re-identification via multi-loss dynamic training,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2019, pp. 8514–8522
2019
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