Beyond triplet loss: A deep quadruplet network for person re-identification

Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017

Volumn 2017-January, Issue , 2017, Pages 1320-1329

  Chen, Weihua ^a,b   Chen, Xiaotang ^a,b   Zhang, Jianguo ^c   Huang, Kaiqi ^a,b,d  

^a CRIPAC and NLPR   (France)

^b UNIVERSITY OF CHINESE ACADEMY OF SCIENCES   (China)

^c UNIVERSITY OF DUNDEE   (United Kingdom)

^d Chinese Academy of Sciences   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ABILITY TESTING; COMPUTER VISION; PATTERN RECOGNITION; SECURITY SYSTEMS;

GENERALIZATION ABILITY; GENERALIZATION CAPABILITY; INTRA-CLASS VARIATION; LEARNING NETWORK; NEGATIVE MININGS; PERSON RE IDENTIFICATIONS; STATE-OF-THE-ART ALGORITHMS; VIDEO SURVEILLANCE;

DEEP LEARNING;

EID: 85044292767     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2017.145     Document Type: Conference Paper

References (45)

1. E. Ahmed, M. Jones, and T. K. Marks. An improved deep learning architecture for person re-identification. In CVPR, 2015.
2. S.-Z. Chen, C.-C. Guo, and J.-H. Lai. Deep ranking for person re-identification via joint representation learning. TIP, 25(5):2353-2367, 2016.
3. W. Chen, X. Chen, J. Zhang, and K. Huang. A multi-task deep network for person re-identification. In AAAI, 2017.
4. 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 CVPR, 2016.
5. C. Cortes and V. Vapnik. Support-vector networks. Machine learning, 20(3):273-297, 1995.
6. J. V. Davis, B. Kulis, P. Jain, S. Sra, and I. S. Dhillon. Information-theoretic metric learning. In ICML, 2007.
7. S. Ding, L. Lin, G. Wang, and H. Chao. Deep feature learning with relative distance comparison for person reidentification. Pattern Recognition, 48(10):2993-3003, 2015.
8. M. Gou, X. Zhang, A. Rates-Borras, S. Asghari-Esfeden, M. Sznaier, and O. Camps. Person re-identification in appearance impaired scenarios. In BMVC, 2016.
9. D. Gray, S. Brennan, and H. Tao. Evaluating appearance models for recognition, reacquisition, and tracking. In Proc. IEEE International Workshop on Performance Evaluation for Tracking and Surveillance (PETS), 2007.
10. R. Hadsell, S. Chopra, and Y. LeCun. Dimensionality reduction by learning an invariant mapping. In CVPR, 2006.
11. M. Hirzer, P. M. Roth, and H. Bischof. Person reidentification by efficient impostor-based metric learning. In Advanced Video and Signal-Based Surveillance (AVSS), 2012 IEEE Ninth International Conference on, 2012.
12. Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long, R. Girshick, S. Guadarrama, and T. Darrell. Caffe: Convolutional architecture for fast feature embedding. In ACM on Multimedia, 2014.
13. S. Karanam, M. Gou, Z. Wu, A. Rates-Borras, O. Camps, and R. J. Radke. A comprehensive evaluation and benchmark for person re-identification: Features, metrics, and datasets. arXiv preprint arXiv:1605.09653, 2016.
14. M. Koestinger, M. Hirzer, P. Wohlhart, P. M. Roth, and H. Bischof. Large scale metric learning from equivalence constraints. In CVPR, 2012.
15. A. Krizhevsky, I. Sutskever, and G. E. Hinton. Imagenet classification with deep convolutional neural networks. In NIPS, 2012.
16. D. Li, X. Chen, Z. Zhang, and K. Huang. Learning deep context-aware features over body and latent parts for person re-identification. In CVPR, 2017.
17. W. Li and X. Wang. Locally aligned feature transforms across views. In CVPR, 2013.
18. W. Li, R. Zhao, and X. Wang. Human reidentification with transferred metric learning. In ACCV, 2012.
19. W. Li, R. Zhao, T. Xiao, and X. Wang. Deepreid: Deep filter pairing neural network for person re-identification. In CVPR, 2014.
20. Z. Li, S. Chang, F. Liang, T. S. Huang, L. Cao, and J. R. Smith. Learning locally-adaptive decision functions for person verification. In CVPR, 2013.
21. S. Liao, Y. Hu, X. Zhu, and S. Z. Li. Person re-identification by local maximal occurrence representation and metric learning. In CVPR, 2015.
22. S. Liao and S. Z. Li. Efficient psd constrained asymmetric metric learning for person re-identification. In ICCV, 2015.
23. T. Matsukawa, T. Okabe, E. Suzuki, and Y. Sato. Hierarchical gaussian descriptor for person re-identification. In CVPR, 2016.
24. S. Paisitkriangkrai, C. Shen, and A. van den Hengel. Learning to rank in person re-identification with metric ensembles. In CVPR, 2015.
25. S. Pedagadi, J. Orwell, S. Velastin, and B. Boghossian. Local fisher discriminant analysis for pedestrian re-identification. In CVPR, 2013.
26. F. Schroff, D. Kalenichenko, and J. Philbin. Facenet: A unified embedding for face recognition and clustering. In CVPR, 2015.
27. Y. Shen, W. Lin, J. Yan, M. Xu, J. Wu, and J. Wang. Person re-identification with correspondence structure learning. In ICCV, 2015.
28. C. Su, F. Yang, S. Zhang, Q. Tian, L. S. Davis, and W. Gao. Multi-task learning with low rank attribute embedding for person re-identification. In ICCV, 2015.
29. C. Su, S. Zhang, J. Xing, W. Gao, and Q. Tian. Deep attributes driven multi-camera person re-identification. In ECCV, 2016.
30. R. R. Varior, M. Haloi, and G. Wang. Gated siamese convolutional neural network architecture for human reidentification. In ECCV, 2016.
31. R. R. Varior, B. Shuai, J. Lu, D. Xu, and G. Wang. A siamese long short-term memory architecture for human reidentification. In ECCV, 2016.
32. F. Wang, W. Zuo, L. Lin, D. Zhang, and L. Zhang. Joint learning of single-image and cross-image representations for person re-identification. In CVPR, 2016.
33. J. Wang, Y. Song, T. Leung, C. Rosenberg, J. Wang, J. Philbin, B. Chen, and Y. Wu. Learning fine-grained image similarity with deep ranking. In CVPR, 2014.
34. Y. Wen, K. Zhang, Z. Li, and Y. Qiao. A discriminative feature learning approach for deep face recognition. In ECCV, 2016.
35. L. Wu, C. Shen, and A. v. d. Hengel. Personnet: person re-identification with deep convolutional neural networks. arXiv preprint arXiv:1601.07255, 2016.
36. L. Wu, C. Shen, and A. van den Hengel. Deep linear discriminant analysis on fisher networks: A hybrid architecture for person re-identification. Pattern Recognition, 2016.
37. T. Xiao, H. Li, W. Ouyang, and X. Wang. Learning deep feature representations with domain guided dropout for person re-identification. In CVPR, 2016.
38. F. Xiong, M. Gou, O. Camps, and M. Sznaier. Person reidentification using kernel-based metric learning methods. In ECCV, 2014.
39. Y. Yang, Z. Lei, S. Zhang, H. Shi, and S. Z. Li. Metric embedded discriminative vocabulary learning for high-level person representation. In AAAI, 2016.
40. Y. Yang, S. Z. Li, L. Wen, and S. Lyu. Unsupervised learning of multi-level descriptors for person re-identification. In AAAI, 2017.
41. D. Yi, Z. Lei, S. Liao, and S. Z. Li. Deep metric learning for person re-identification. In ICPR, 2014.
42. L. Zhang, T. Xiang, and S. Gong. Learning a discriminative null space for person re-identification. In CVPR, 2016.
43. R. Zhao, W. Ouyang, and X. Wang. Unsupervised salience learning for person re-identification. In CVPR, 2013.
44. R. Zhao, W. Ouyang, and X. Wang. Learning mid-level filters for person re-identification. In CVPR, 2014.
45. L. Zheng, Y. Yang, and A. G. Hauptmann. Person reidentification: Past, present and future. arXiv preprint arXiv:1610.02984, 2016.