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structures for re-identification. In: British machine vision conference, Dundee, pp
1–11
10. Liao S, Hu Y, Zhu X, Li SZ (2015) Person re-identification by local maximal
occurrence representation and metric learning. In: IEEE conference on computer
vision and pattern recognition, Boston, pp 2197–2206
11. Tan S, Zheng F, Shao L (2015) Dense invariant feature based support vector ranking for person re-identification. In: IEEE global conference on signal and information processing, Orlando, pp 687–691
12. Zheng L, Shen L, Tian L, Wang S, Wang J, Tian Q (2015) Scalable person reidentification: a benchmark. In: IEEE international conference on computer vision,
Santiago, pp 1116–1124
13. Li W, Zhao R, Xiao T, Wang X (2015) DeepReID: deep filter pairing neural network
for person re-identification. In: IEEE conference on computer vision and pattern
recognition, Boston, pp 152–159
14. Ristani E, Solera F, Zou R, Cucchiara R, Tomasi C (2016) Performance measures
and a data set for multi-target, multi-camera tracking. In: European conference on
computer vision, Amsterdam, pp 17–35
15. Ding S, Lin L, Wang G, Chao H (2015) Deep feature learning with relative distance
comparison for person re-identification. Pattern Recognit 48(10):2993–3003
16. Su C, Li J, Zhang S, Xing J, Gao W, Tian Q (2017) Pose-driven deep convolutional
model for person re-identification. In: IEEE international conference on computer
vision, Venice, pp 3980–3989
17. Geng M, Wang Y, Xiang T, Tian Y (2018) Deep transfer learning for person reidentification. In: IEEE international conference on multimedia big data, Xian, pp
1–5
18. Yao H, Zhang S, Zhang Y, Li J, Tian Q (2019) Deep representation learning with
part loss for person re-identification. IEEE Trans Image Process 28(6):2860–2871
19. He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition.
In: IEEE conference on computer vision and pattern recognition, Las Vegas, pp
770–778
20. Cheng D, Gong Y, Zhou S, Wang J, Zheng N (2016) Person re-identification by
multi-channel parts-based CNN with improved triplet loss function. In: IEEE conference on computer vision and pattern recognition, Las Vegas, pp 1335–1344
21. Zheng Z, Zheng L, Yang Y (2018) A discriminatively learned CNN embedding for
person re-identification. ACM Trans Multimed Comput 14(1):13
22. Sun Y, Zheng L, Yang Y, Tian Q, Wang S (2018) Beyond part models: person
retrieval with refined part pooling. In: European conference on computer vision,
Munich, pp 480–496
457
9. Cheng DS, Cristani M, Stoppa M, Bazzani L, Murino V (2011) Custom pictorial
structures for re-identification. In: British machine vision conference, Dundee, pp
1–11
10. Liao S, Hu Y, Zhu X, Li SZ (2015) Person re-identification by local maximal
occurrence representation and metric learning. In: IEEE conference on computer
vision and pattern recognition, Boston, pp 2197–2206
11. Tan S, Zheng F, Shao L (2015) Dense invariant feature based support vector ranking for person re-identification. In: IEEE global conference on signal and information processing, Orlando, pp 687–691
12. Zheng L, Shen L, Tian L, Wang S, Wang J, Tian Q (2015) Scalable person reidentification: a benchmark. In: IEEE international conference on computer vision,
Santiago, pp 1116–1124
13. Li W, Zhao R, Xiao T, Wang X (2015) DeepReID: deep filter pairing neural network
for person re-identification. In: IEEE conference on computer vision and pattern
recognition, Boston, pp 152–159
14. Ristani E, Solera F, Zou R, Cucchiara R, Tomasi C (2016) Performance measures
and a data set for multi-target, multi-camera tracking. In: European conference on
computer vision, Amsterdam, pp 17–35
15. Ding S, Lin L, Wang G, Chao H (2015) Deep feature learning with relative distance
comparison for person re-identification. Pattern Recognit 48(10):2993–3003
16. Su C, Li J, Zhang S, Xing J, Gao W, Tian Q (2017) Pose-driven deep convolutional
model for person re-identification. In: IEEE international conference on computer
vision, Venice, pp 3980–3989
17. Geng M, Wang Y, Xiang T, Tian Y (2018) Deep transfer learning for person reidentification. In: IEEE international conference on multimedia big data, Xian, pp
1–5
18. Yao H, Zhang S, Zhang Y, Li J, Tian Q (2019) Deep representation learning with
part loss for person re-identification. IEEE Trans Image Process 28(6):2860–2871
19. He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition.
In: IEEE conference on computer vision and pattern recognition, Las Vegas, pp
770–778
20. Cheng D, Gong Y, Zhou S, Wang J, Zheng N (2016) Person re-identification by
multi-channel parts-based CNN with improved triplet loss function. In: IEEE conference on computer vision and pattern recognition, Las Vegas, pp 1335–1344
21. Zheng Z, Zheng L, Yang Y (2018) A discriminatively learned CNN embedding for
person re-identification. ACM Trans Multimed Comput 14(1):13
22. Sun Y, Zheng L, Yang Y, Tian Q, Wang S (2018) Beyond part models: person
retrieval with refined part pooling. In: European conference on computer vision,
Munich, pp 480–496