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A big challenge of person re-identification (Re-ID) using a multi-branch network architecture is to learn diverse features from the ID-labeled dataset.
N. Srivastava, G. Hinton, A. Krizhevsky, I. Sutskever, and R. Salakhutdinov, “Dropout: a simple way to prevent neural networks from overfitting,” The Journal of Machine Learning Research , vol. 15, no. 1, pp. 1929–1958, 2014
2014
Earlier work this paper cites.
W. Li, R. Zhao, T. Xiao, and X. Wang, “Deepreid: Deep filter pairing neural network for person re-identification,” in 2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , June 2014, pp. 152–159
2014
Earlier work this paper cites.
J. Tompson, R. Goroshin, A. Jain, Y. LeCun, and C. Bregler, “Efficient object localization using convolutional networks,” in 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , June 2015, pp. 648–656
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 2015 IEEE International Conference on Computer Vision (ICCV) , Dec 2015, pp. 1116–1124
2015
Earlier work this paper cites.
2016
Earlier work this paper cites.
C. Su, S. Zhang, J. Xing, W. Gao, and Q. Tian, “Deep attributes driven multi-camera person re-identification,” in Proceedings of the European Conference on Computer Vision (ECCV) . Springer, 2016, pp. 475–491
2016
Earlier work this paper cites.
D. Cheng, Y. Gong, S. Zhou, J. Wang, and N. Zheng, “Person re-identification by multi-channel parts-based cnn with improved triplet loss function,” in 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , June 2016, pp. 1335–1344
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 Proceedings of the European Conference on Computer Vision (ECCV) . 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 Proceedings of the European Conference on Computer Vision (ECCV) . Springer, 2016, pp. 17–35
2016
Earlier work this paper cites.
C. Su, J. Li, S. Zhang, J. Xing, W. Gao, and Q. Tian, “Pose-driven deep convolutional model for person re-identification,” in 2017 IEEE Proceedings on International Conference on Computer Vision (ICCV) , 2017, pp. 3960–3969
2017
Earlier work this paper cites.
W. Chen, X. Chen, J. Zhang, and K. Huang, “Beyond triplet loss: A deep quadruplet network for person re-identification,” in 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , July 2017, pp. 1320–1329
2017
Earlier work this paper cites.
S. Bai, X. Bai, and Q. Tian, “Scalable person re-identification on supervised smoothed manifold,” in 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , July 2017, pp. 3356–3365
2017
Earlier work this paper cites.
2017
Earlier work this paper cites.
L. Zhao, X. Li, Y. Zhuang, and J. Wang, “Deeply-learned part-aligned representations for person re-identification,” in 2017 IEEE International Conference on Computer Vision (ICCV) , Oct 2017, pp. 3239–3248
2017
Earlier work this paper cites.
V. Kumar, A. Namboodiri, M. Paluri, and C. V. Jawahar, “Pose-aware person recognition,” in 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , July 2017, pp. 6797–6806
2017
Earlier work this paper cites.
2017
Earlier work this paper cites.
2017
Earlier work this paper cites.
W. Chen, X. Chen, J. Zhang, and K. Huang, “A multi-task deep network for person re-identification,” in Thirty-First AAAI Conference on Artificial Intelligence , 2017
2017
Earlier work this paper cites.
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, and I. Polosukhin, “Attention is all you need,” in Advances in Neural Information Processing Systems , 2017, pp. 5998–6008
2017
Cited alongside, same era.
Z. Zhong, L. Zheng, D. Cao, and S. Li, “Re-ranking person re-identification with k-reciprocal encoding,” in 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , July 2017, pp. 3652–3661
2017
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.
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.
2018
Later among the works it cites.
Y. Wang, L. Wang, Y. You, X. Zou, V. Chen, S. Li, G. Huang, B. Hariharan, and K. Q. Weinberger, “Resource aware person re-identification across multiple resolutions,” in 2018 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , June 2018, pp. 8042–8051
2018
Later among the works it cites.
2018
Later among the works it cites.
Z. Dai, M. Chen, X. Gu, S. Zhu, and P. Tan, “Batch dropblock network for person re-identification and beyond,” in 2019 IEEE Proceedings on International Conference on Computer Vision (ICCV) , 2019, pp. 3691–3701
2019
Later among the works it cites.
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2018
Cited alongside, same era.
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
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.
Y. Suh, J. Wang, S. Tang, T. Mei, and K. Mu Lee, “Part-aligned bilinear representations for person re-identification,” in Proceedings of the European Conference on Computer Vision (ECCV) , 2018, pp. 402–419
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.
G. Ghiasi, T.-Y. Lin, and Q. V. Le, “Dropblock: A regularization method for convolutional networks,” in Advances in Neural Information Processing Systems , 2018, pp. 10 727–10 737
2018
Cited alongside, same era.
J. Xu, R. Zhao, F. Zhu, H. Wang, and W. Ouyang, “Attention-aware compositional network for person re-identification,” in 2018 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , June 2018, pp. 2119–2128
2018
Cited alongside, same era.
M. S. Sarfraz, A. Schumann, A. Eberle, and R. Stiefelhagen, “A pose-sensitive embedding for person re-identification with expanded cross neighborhood re-ranking,” in 2018 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , June 2018, pp. 420–429
2018
Cited alongside, same era.
B. Chen, W. Deng, and J. Hu, “Mixed high-order attention network for person re-identification,” in 2019 IEEE Proceedings on International Conference on Computer Vision (ICCV) , 2019, pp. 371–381
2019
Later among the works it cites.
W. Yang, H. Huang, Z. Zhang, X. Chen, K. Huang, and S. Zhang, “Towards rich feature discovery with class activation maps augmentation for person re-identification,” in 2019 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , June 2019, pp. 1389–1398
2019
Later among the works it cites.
R. Hou, B. Ma, H. Chang, X. Gu, S. Shan, and X. Chen, “Interaction-and-aggregation network for person re-identification,” in 2019 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , 2019, pp. 9317–9326
2019
Later among the works it cites.
T. Chen, S. Ding, J. Xie, Y. Yuan, W. Chen, Y. Yang, Z. Ren, and Z. Wang, “Abd-net: Attentive but diverse person re-identification,” in 2019 IEEE Proceedings on International Conference on Computer Vision (ICCV) , 2019, pp. 8351–8361
2019
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 2018 IEEE Conference on Computer Vision and Pattern Recognition WorkShops (CVPRW) , 2019, pp. 4321–4329
2019
Later among the works it cites.
L. Wei, S. Zhang, H. Yao, W. Gao, and Q. Tian, “Glad: Global-local-alignment descriptor for scalable person re-identification,” IEEE Trans. Multimedia , vol. 21, pp. 986 – 999, Apr. 2019
2019
Later among the works it cites.
H. He, Z. Zhang, H. Zhang, Z. Zhang, J. Xie, and M. Li, “Bag of tricks for image classification with convolutional neural networks,” in 2019 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , 2019, pp. 558–567
2019
Later among the works it cites.
H. Yao, S. Zhang, R. Hong, Y. Zhang, C. Xu, and Q. Tian, “Deep representation learning with part loss for person re-identification,” IEEE Transactions on Image Processing , vol. 28, no. 6, pp. 2860–2871, June 2019
2019
Later among the works it cites.
L. Zheng, Y. Huang, H. Lu, and Y. Yang, “Pose-invariant embedding for deep person re-identification,” IEEE Transactions on Image Processing , vol. 28, no. 9, pp. 4500–4509, Sep. 2019
2019
Later among the works it cites.
B. N. Xia, Y. Gong, Y. Zhang, and C. Poellabauer, “Second-order non-local attention networks for person re-identification,” in 2019 IEEE Proceedings on International Conference on Computer Vision (ICCV) , 2019, pp. 3760–3769
2019
Later among the works it cites.
R. Quan, X. Dong, Y. Wu, L. Zhu, and Y. Yang, “Auto-reid: Searching for a part-aware convnet for person re-identification,” in 2019 IEEE Proceedings on International Conference on Computer Vision (ICCV) , 2019
2019
Later among the works it cites.
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 2019 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , June 2019
2019
Later among the works it cites.
C. Zhao, X. Lv, Z. Zhang, W. Zuo, J. Wu, and D. Miao, “Deep fusion feature representation learning with hard mining center-triplet loss for person re-identification,” IEEE Trans. Multimedia , vol. -, pp. 1 – 16, Early-Access 2020
2020
Closest in time.