1 |
LAYNE R, HOSPEDALES T, GONG S G. Person re-identification by attributes [C]// Proceedings of the 2012 British Machine Vision Conference. Durham: BMVA Press, 2012: No.24. 10.5244/c.26.24
|
2 |
WANG J Y, ZHU X T, GONG S G, et al. Transferable joint attribute-identity deep learning for unsupervised person re-identification [C]// Proceedings of the 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Piscataway: IEEE, 2018: 2275-2284. 10.1109/cvpr.2018.00242
|
3 |
KUMAR N, BERG A C, BELHUMEUR P N, et al. Attribute and simile classifiers for face verification [C]// Proceedings of the 2009 IEEE 12th International Conference on Computer Vision. Piscataway: IEEE, 2009: 365-372. 10.1109/iccv.2009.5459250
|
4 |
FERIS R, BOBBITT R, BROWN L, et al. Attribute-based people search: lessons learnt from a practical surveillance system [C]// Proceedings of the 4th ACM International Conference on Multimedia Retrieval. New York: ACM, 2014: 153-160. 10.1145/2578726.2578732
|
5 |
LIN Y T, ZHENG L, ZHENG Z D, et al. Improving person re-identification by attribute and identity learning[J]. Pattern Recognition, 2019, 95: 151-161. 10.1016/j.patcog.2019.06.006
|
6 |
马路宽.行人属性识别研究[J].现代计算机, 2021(4): 89-93. 10.3969/j.issn.1007-1423.2021.04.018
|
|
MA L K. Research on pedestrian attribute recognition[J]. Modern Computer, 2021(4): 89-93. 10.3969/j.issn.1007-1423.2021.04.018
|
7 |
LI D W, CHEN X T, HUANG K Q. Multi-attribute learning for pedestrian attribute recognition in surveillance scenarios [C]// Proceedings of the 3rd IAPR Asian Conference on Pattern Recognition. Piscataway: IEEE, 2015: 111-115. 10.1109/acpr.2015.7486476
|
8 |
SUDOWE P, SPITZER H, LEIBE B. Person attribute recognition with a jointly-trained holistic CNN model [C]// Proceedings of the 2015 IEEE International Conference on Computer Vision Workshops. Piscataway: IEEE, 2015: 329-337. 10.1109/iccvw.2015.51
|
9 |
ABDULNABI A H, WANG G, LU J W, et al. Multi-task CNN model for attribute prediction[J]. IEEE Transactions on Multimedia, 2015, 17(11): 1949-1959. 10.1109/tmm.2015.2477680
|
10 |
LI D W, CHEN X T, ZHANG Z, et al. Pose guided deep model for pedestrian attribute recognition in surveillance scenarios [C]// Proceedings of the 2018 IEEE International Conference on Multimedia and Expo. Piscataway: IEEE, 2018: 1-6. 10.1109/icme.2018.8486604
|
11 |
SARAFIANOS N, XU X, KAKADIARIS I A. Deep imbalanced attribute classification using visual attention aggregation [C]// Proceedings of the 2018 European Conference on Computer Vision, LNCS 11215. Cham: Springer, 2018: 708-725.
|
12 |
BOURDEV L, MAJI S, MALIK J. Describing people: a poselet-based approach to attribute classification [C]// Proceedings of the 2011 International Conference on Computer Vision. Piscataway: IEEE, 2011: 1543-1550. 10.1109/iccv.2011.6126413
|
13 |
LIU X H, ZHAO H Y, TIAN M Q, et al. HydraPlus-Net: attentive deep features for pedestrian analysis [C]// Proceedings of the 2017 IEEE International Conference on Computer Vision. Piscataway: IEEE, 2017: 350-359. 10.1109/iccv.2017.46
|
14 |
WU M D, HUANG D, GUO Y F, et al. Distraction-aware feature learning for human attribute recognition via coarse-to-fine attention mechanism [C]// Proceedings of the 34th AAAI Conference on Artificial Intelligence. Palo Alto, CA: AAAI Press, 2020: 12394-12401. 10.1609/aaai.v34i07.6925
|
15 |
YAGHOUBI E, BORZA D, NEVES J, et al. An attention-based deep learning model for multiple pedestrian attributes recognition[J]. Image and Vision Computing, 2020, 102: No.103981. 10.1016/j.imavis.2020.103981
|
16 |
吴锐,刘宇,冯凯.基于双域自注意力机制的行人属性识别[J].计算机应用, 2021, 41(2): 372-378.
|
|
WU R, LIU Y, FENG K. Pedestrian attribute recognition based on two-domain self-attention mechanism[J]. Journal of Computer Applications, 2021, 41(2): 372-378.
|
17 |
HE K M, ZHANG X Y, REN S Q, et al. Deep residual learning for image recognition [C]// Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition. Piscataway: IEEE, 2016, 770-778. 10.1109/cvpr.2016.90
|
18 |
DENG Y B, LUO P, LOY C C, et al. Pedestrian attribute recognition at far distance [C]// Proceedings of the 22nd ACM International Conference on Multimedia. New York: ACM, 2014: 789-792. 10.1145/2647868.2654966
|
19 |
LI D W, ZHANG Z, CHEN X T, et al. A richly annotated dataset for pedestrian attribute recognition[EB/OL]. (2016-04-27) [2021-08-15]. . 10.1109/tip.2018.2878349
|
20 |
LI D W, ZHANG Z, CHEN X T, et al. A richly annotated pedestrian dataset for person retrieval in real surveillance scenarios[J]. IEEE Transactions on Image Processing, 2019, 28(4): 1575-1590. 10.1109/tip.2018.2878349
|
21 |
刘士豪,胡学敏,姜博厚,等.基于生成对抗双网络的虚拟到真实驾驶场景的视频翻译模型[J].计算机应用, 2020, 40(6): 1621-1626.
|
|
LIU S H, HU X M, JIANG B H, et al. Video translation model from virtual to real driving scenes based on generative adversarial dual networks[J]. Journal of Computer Applications, 2020, 40(6): 1621-1626.
|
22 |
ZHU J Y, PARK T, ISOLA P, et al. Unpaired image-to-image translation using cycle-consistent adversarial networks [C]// Proceedings of the 2017 IEEE International Conference on Computer Vision. Piscataway: IEEE, 2017: 2242-2251. 10.1109/iccv.2017.244
|
23 |
HAN K, WANG Y H, SHU H, et al. Attribute aware pooling for pedestrian attribute recognition [C]// Proceedings of the 28th Joint Conference on Artificial Intelligence. California: ijcai.org, 2019: 2456-2462. 10.24963/ijcai.2019/341
|
24 |
TANG C F, SHENG L, ZHANG Z X, et al. Improving pedestrian attribute recognition with weakly-supervised multi-scale attribute-specific localization [C]// Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision. Piscataway: IEEE, 2019: 4996-5005. 10.1109/iccv.2019.00510
|
25 |
ZENG H T, AI H Z, ZHUANG Z J, et al. Multi-task learning via co-attentive sharing for pedestrian attribute recognition [C]// Proceedings of the 2020 IEEE International Conference on Multimedia and Expo. Piscataway: IEEE, 2020: 1-6. 10.1109/icme46284.2020.9102757
|
26 |
MOGHADDAM M, CHARMI M, HASSANPOOR H. Jointly human semantic parsing and attribute recognition with feature pyramid structure in EfficientNets[J]. IET Image Processing, 2021, 15(10): 2281-2291.
|
27 |
JIA J, HUANG H J, YANG W J, et al. Rethinking of pedestrian attribute recognition: realistic datasets with efficient method [EB/OL]. (2020-05-26) [2021-08-15]. .
|