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Most person re-identification methods, being supervised techniques, suffer from the burden of massive annotation requirement.
Z. Shen, J. Li, Z. Su, M. Li, Y. Chen, Y.-G. Jiang, and X. Xue, “Weakly supervised dense video captioning,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2017, pp. 1916–1924
1924
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2007
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J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei, “Imagenet: A large-scale hierarchical image database,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2009, pp. 248–255
2009
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S. Ren, K. He, R. Girshick, and J. Sun, “Faster r-cnn: Towards real-time object detection with region proposal networks,” in Advances in Neural Information Processing Systems , 2015, pp. 91–99
2015
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H. Wang, S. Gong, X. Zhu, and T. Xiang, “Human-in-the-loop person re-identification,” in Proceedings of the European Conference on Computer Vision . Springer, 2016, pp. 405–422
2016
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H. Bilen and A. Vedaldi, “Weakly supervised deep detection networks,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2016, pp. 2846–2854
2016
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L. Zheng, Z. Bie, Y. Sun, J. Wang, C. Su, S. Wang, and Q. Tian, “Mars: A video benchmark for large-scale person re-identification,” in Proceedings of the European Conference on Computer Vision , 2016, pp. 868–884
2016
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M. Ye, A. J. Ma, L. Zheng, J. Li, and P. C. Yuen, “Dynamic label graph matching for unsupervised video re-identification,” in Proceedings of the IEEE International Conference on Computer Vision , 2017, pp. 5142–5150
2017
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S. Bak and P. Carr, “One-shot metric learning for person re-identification,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2017, pp. 2990–2999
2017
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T.-Y. Lin, P. Dollár, R. Girshick, K. He, B. Hariharan, and S. Belongie, “Feature pyramid networks for object detection,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2017, pp. 2117–2125
2017
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A. Khoreva, R. Benenson, J. Hosang, M. Hein, and B. Schiele, “Simple does it: Weakly supervised instance and semantic segmentation,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2017, pp. 876–885
2017
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L. Chen, M. Zhai, and G. Mori, “Attending to distinctive moments: Weakly-supervised attention models for action localization in video,” in Proceedings of the IEEE International Conference on Computer Vision Workshops , 2017, pp. 328–336
2017
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R. Panda, A. Das, Z. Wu, J. Ernst, and A. K. Roy-Chowdhury, “Weakly supervised summarization of web videos,” in Proceedings of the IEEE International Conference on Computer Vision , 2017, pp. 3657–3666
2017
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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 , 2018, pp. 480–496
2018
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J. Si, H. Zhang, C.-G. Li, J. Kuen, X. Kong, A. C. Kot, and G. Wang, “Dual attention matching network for context-aware feature sequence based person re-identification,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2018, pp. 5363–5372
2018
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H. Fan, L. Zheng, C. Yan, and Y. Yang, “Unsupervised person re-identification: Clustering and fine-tuning,” ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) , vol. 14, no. 4, p. 83, 2018
2018
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M. Li, X. Zhu, and S. Gong, “Unsupervised person re-identification by deep learning tracklet association,” in Proceedings of the European Conference on Computer Vision , 2018, pp. 737–753
2018
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Y. Wu, Y. Lin, X. Dong, Y. Yan, W. Ouyang, and Y. Yang, “Exploit the unknown gradually: One-shot video-based person re-identification by stepwise learning,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2018, pp. 5177–5186
2018
Cited alongside, same era.
S. Roy, S. Paul, N. E. Young, and A. K. Roy-Chowdhury, “Exploiting transitivity for learning person re-identification models on a budget,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2018, pp. 7064–7072
2018
Cited alongside, same era.
D. Chen, H. Li, X. Liu, Y. Shen, J. Shao, Z. Yuan, and X. Wang, “Improving deep visual representation for person re-identification by global and local image-language association,” in Proceedings of the European Conference on Computer Vision , 2018, pp. 54–70
2018
Cited alongside, same era.
D. Chen, H. Li, T. Xiao, S. Yi, and X. Wang, “Video person re-identification with competitive snippet-similarity aggregation and co-attentive snippet embedding,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2018, pp. 1169–1178
Y. Wu, Y. Lin, X. Dong, Y. Yan, W. Bian, and Y. Yang, “Progressive learning for person re-identification with one example,” IEEE Transactions on Image Processing , vol. 28, no. 6, pp. 2872–2881, 2019
2019
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Z. Liu, J. Wang, S. Gong, H. Lu, and D. Tao, “Deep reinforcement active learning for human-in-the-loop person re-identification,” in Proceedings of the IEEE International Conference on Computer Vision , 2019, pp. 6122–6131
2019
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X. Zhu, X. Zhu, M. Li, V. Murino, and S. Gong, “Intra-camera supervised person re-identification: A new benchmark,” in Proceedings of the IEEE International Conference on Computer Vision Workshops , 2019
2019
Later among the works it cites.
2019
Later among the works it cites.
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2018
Cited alongside, same era.
J. Ahn and S. Kwak, “Learning pixel-level semantic affinity with image-level supervision for weakly supervised semantic segmentation,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2018, pp. 4981–4990
2018
Cited alongside, same era.
S. Paul, S. Roy, and A. K. Roy-Chowdhury, “W-talc: Weakly-supervised temporal activity localization and classification,” in Proceedings of the European Conference on Computer Vision , 2018, pp. 563–579
2018
Cited alongside, same era.
S. Cai, W. Zuo, L. S. Davis, and L. Zhang, “Weakly-supervised video summarization using variational encoder-decoder and web prior,” in Proceedings of the European Conference on Computer Vision , 2018, pp. 184–200
2018
Cited alongside, same era.
G. Chen, J. Lu, M. Yang, and J. Zhou, “Spatial-temporal attention-aware learning for video-based person re-identification,” IEEE Transactions on Image Processing , vol. 28, no. 9, pp. 4192–4205, 2019
2019
Cited alongside, same era.
G. Chen, C. Lin, L. Ren, J. Lu, and J. Zhou, “Self-critical attention learning for person re-identification,” in Proceedings of the IEEE International Conference on Computer Vision , 2019, pp. 9637–9646
2019
Cited alongside, same era.
J. Meng, S. Wu, and W.-S. Zheng, “Weakly supervised person re-identification,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2019, pp. 760–769
2019
Cited alongside, same era.
M. Ye, J. Li, A. J. Ma, L. Zheng, and P. C. Yuen, “Dynamic graph co-matching for unsupervised video-based person re-identification,” IEEE Transactions on Image Processing , vol. 28, no. 6, pp. 2976–2990, 2019
2019
Cited alongside, same era.
Y. Rao, J. Lu, and J. Zhou, “Learning discriminative aggregation network for video-based face recognition and person re-identification,” International Journal of Computer Vision , vol. 127, no. 6-7, pp. 701–718, 2019
2019
Cited alongside, same era.
S. Jin, W. Liu, W. Ouyang, and C. Qian, “Multi-person articulated tracking with spatial and temporal embeddings,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2019, pp. 5664–5673
2019
Later among the works it cites.
F. Heidarivincheh, M. Mirmehdi, and D. Damen, “Weakly-supervised completion moment detection using temporal attention,” in Proceedings of the IEEE International Conference on Computer Vision Workshops , 2019
2019
Later among the works it cites.
T. Yu, Z. Ren, Y. Li, E. Yan, N. Xu, and J. Yuan, “Temporal structure mining for weakly supervised action detection,” in Proceedings of the IEEE International Conference on Computer Vision , 2019, pp. 5522–5531
2019
Later among the works it cites.
N. C. Mithun, S. Paul, and A. K. Roy-Chowdhury, “Weakly supervised video moment retrieval from text queries,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2019, pp. 11 592–11 601
2019
Later among the works it cites.
P. X. Nguyen, D. Ramanan, and C. C. Fowlkes, “Weakly-supervised action localization with background modeling,” in Proceedings of the IEEE International Conference on Computer Vision , 2019, pp. 5502–5511
2019
Later among the works it cites.
Y. Yan, Q. Zhang, B. Ni, W. Zhang, M. Xu, and X. Yang, “Learning context graph for person search,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2019, pp. 2158–2167
2019
Later among the works it cites.
J. Xiao, Y. Xie, T. Tillo, K. Huang, Y. Wei, and J. Feng, “Ian: the individual aggregation network for person search,” Pattern Recognition , vol. 87, pp. 332–340, 2019
2019
Later among the works it cites.
C. Han, J. Ye, Y. Zhong, X. Tan, C. Zhang, C. Gao, and N. Sang, “Re-id driven localization refinement for person search,” in Proceedings of the IEEE International Conference on Computer Vision , 2019, pp. 9814–9823
2019
Later among the works it cites.
Q. Dong, X. Zhu, and S. Gong, “Single-label multi-class image classification by deep logistic regression,” in Proceedings of the AAAI Conference on Artificial Intelligence , vol. 33, 2019, pp. 3486–3493
2019
Later among the works it cites.
M. Ye and P. C. Yuen, “Purifynet: A robust person re-identification model with noisy labels,” IEEE Transactions on Information Forensics and Security , vol. 15, pp. 2655–2666, 2020
2020
Closest in time.
G. Chen, J. Lu, M. Yang, and J. Zhou, “Learning recurrent 3d attention for video-based person re-identification,” IEEE Transactions on Image Processing , 2020
2020
Closest in time.
H.-X. Yu and W.-S. Zheng, “Weakly supervised discriminative feature learning with state information for person identification,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2020, pp. 5528–5538
2020
Closest in time.