Journal of Computer Applications ›› 2023, Vol. 43 ›› Issue (7): 2182-2189.DOI: 10.11772/j.issn.1001-9081.2022060827
Special Issue: 人工智能
• Artificial intelligence • Previous Articles Next Articles
Jiaming HE1, Jucheng YANG1(), Chao WU1, Xiaoning YAN2, Nenghua XU2
Received:
2022-06-10
Revised:
2022-09-02
Accepted:
2022-09-09
Online:
2022-10-11
Published:
2023-07-10
Contact:
Jucheng YANG
About author:
HE Jiaming, born in 1995, M. S. candidate. His research interests include person re-identification.通讯作者:
杨巨成
作者简介:
何嘉明(1995—),男,广东清远人,硕士研究生,CCF会员,主要研究方向:行人重识别;CLC Number:
Jiaming HE, Jucheng YANG, Chao WU, Xiaoning YAN, Nenghua XU. Person re-identification method based on multi-modal graph convolutional neural network[J]. Journal of Computer Applications, 2023, 43(7): 2182-2189.
何嘉明, 杨巨成, 吴超, 闫潇宁, 许能华. 基于多模态图卷积神经网络的行人重识别方法[J]. 《计算机应用》唯一官方网站, 2023, 43(7): 2182-2189.
Add to citation manager EndNote|Ris|BibTeX
URL: https://www.joca.cn/EN/10.11772/j.issn.1001-9081.2022060827
方法 | Market-1501 | DukeMTMC-reID | ||
---|---|---|---|---|
mAP | Rank-1 | mAP | Rank-1 | |
HA-CNN[ | 75.7 | 91.2 | 63.8 | 80.5 |
PCB[ | 77.3 | 92.4 | 69.2 | 83.3 |
OSNet[ | 84.9 | 94.8 | 73.5 | 88.6 |
APR[ | 66.9 | 87.0 | 55.5 | 73.9 |
ACRN[ | 62.6 | 83.4 | 52.0 | 72.6 |
AANet[ | 82.5 | 93.9 | 72.6 | 86.4 |
SGGNN[ | 82.8 | 92.3 | 68.2 | 81.1 |
MGAT[ | 76.5 | 91.5 | — | — |
HOReID[ | 84.9 | 94.2 | 75.6 | 86.9 |
CLFA[ | 85.9 | 94.5 | 76.4 | 86.4 |
DCC[ | 88.6 | — | — | — |
Base-CNN(本文方法) | 85.6 | 94.2 | 76.2 | 86.3 |
MMGCN(本文方法) | 87.6 | 95.1 | 77.3 | 88.4 |
Tab. 1 Comparison of experimental results on Market-1501 and DukeMTMC-reID datasets
方法 | Market-1501 | DukeMTMC-reID | ||
---|---|---|---|---|
mAP | Rank-1 | mAP | Rank-1 | |
HA-CNN[ | 75.7 | 91.2 | 63.8 | 80.5 |
PCB[ | 77.3 | 92.4 | 69.2 | 83.3 |
OSNet[ | 84.9 | 94.8 | 73.5 | 88.6 |
APR[ | 66.9 | 87.0 | 55.5 | 73.9 |
ACRN[ | 62.6 | 83.4 | 52.0 | 72.6 |
AANet[ | 82.5 | 93.9 | 72.6 | 86.4 |
SGGNN[ | 82.8 | 92.3 | 68.2 | 81.1 |
MGAT[ | 76.5 | 91.5 | — | — |
HOReID[ | 84.9 | 94.2 | 75.6 | 86.9 |
CLFA[ | 85.9 | 94.5 | 76.4 | 86.4 |
DCC[ | 88.6 | — | — | — |
Base-CNN(本文方法) | 85.6 | 94.2 | 76.2 | 86.3 |
MMGCN(本文方法) | 87.6 | 95.1 | 77.3 | 88.4 |
1 | KHAMIS S, KUO C H, SINGH V K, et al. Joint learning for attribute-consistent person re-identification [C]// Proceedings of the 2014 European Conference on Computer Vision, LNCS 8927. Cham: Springer, 2015: 134-146. |
2 | KÖSTINGER M, HIRZER M, WOHLHART P, et al. Large scale metric learning from equivalence constraints [C]// Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition. Piscataway: IEEE, 2012: 2288-2295. 10.1109/cvpr.2012.6247939 |
3 | LI W, WANG X G. Locally aligned feature transforms across views [C]// Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition. Piscataway: IEEE, 2013: 3594-3601. 10.1109/cvpr.2013.461 |
4 | ZHENG W S, GONG S G, XIANG T. Reidentification by relative distance comparison[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013, 35(3): 653-668. 10.1109/tpami.2012.138 |
5 | DALAL N, TRIGGS B. Histograms of oriented gradients for human detection [C]// Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition — Volume 1. Piscataway: IEEE, 2005: 886-893. 10.1109/cvpr.2005.4 |
6 | LOWE D G. Object recognition from local scale-invariant features [C]// Proceedings of the 7th IEEE International Conference on Computer Vision — Volume 2. Piscataway: IEEE, 1999: 1150-1157. 10.1109/iccv.1999.790410 |
7 | WU Z H, PAN S R, CHEN F W, et al. A comprehensive survey on graph neural networks[J]. IEEE Transactions on Neural Networks and Learning Systems, 2021, 32(1): 4-24. 10.1109/tnnls.2020.2978386 |
8 | 杨永胜,邓淼磊,李磊,等.基于深度学习的行人重识别综述[J].计算机工程与应用, 2022, 58(9): 51-66. 10.3778/j.issn.1002-8331.2110-0300 |
YANG Y S, DENG M L, LI L, et al. Overview of pedestrian re-identification based on deep learning[J]. Computer Engineering and Applications, 2022, 58(9): 51-66. 10.3778/j.issn.1002-8331.2110-0300 | |
9 | 杨锋,许玉,尹梦晓,等.基于深度学习的行人重识别综述[J].计算机应用, 2020, 40(5): 1243-1252. 10.11772/j.issn.1001-9081.2019091703 |
YANG F, XU Y, YIN M X, et al. Review on deep learning-based pedestrian re-identification[J]. Journal of Computer Applications, 2020, 40(5): 1243-1252. 10.11772/j.issn.1001-9081.2019091703 | |
10 | 罗浩,姜伟,范星,等.基于深度学习的行人重识别研究进展[J].自动化学报, 2019, 45(11): 2032-2049. 10.16383/j.aas.c180154 |
LUO H, JIANG W, FAN X, et al. A survey on deep learning based person re-identification[J]. Acta Automatica Sinica, 2019, 45(11): 2032-2049. 10.16383/j.aas.c180154 | |
11 | LI W, ZHAO R, XIAO T, et al. DeepReID: deep filter pairing neural network for person re-identification [C]// Proceedings of the 2014 IEEE Conference on Computer Vision and Pattern Recognition. Piscataway: IEEE, 2014: 152-159. 10.1109/cvpr.2014.27 |
12 | SUN Y F, ZHENG L, YANG Y, et al. Beyond part models: person retrieval with refined part pooling (and a strong convolutional baseline) [C]// Proceedings of the 2018 European Conference on Computer Vision, LNCS 11208. Cham: Springer, 2018: 501-518. |
13 | ZHOU K Y, YANG Y X, CAVALLARO A, et al. Omni-scale feature learning for person re-identification [C]// Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision. Piscataway: IEEE, 2019: 3701-3711. 10.1109/iccv.2019.00380 |
14 | 邓轩,廖开阳,郑元林,等.基于深度多视图特征距离学习的行人重识别[J].计算机应用, 2019, 39(8): 2223-2229. 10.11772/j.issn.1001-9081.2018122505 |
DENG X, LIAO K Y, ZHENG Y L, et al. Person re-identification based on deep multi-view feature distance learning[J]. Journal of Computer Applications, 2019, 39(8): 2223-2229. 10.11772/j.issn.1001-9081.2018122505 | |
15 | LI W, ZHU X T, GONG S G. Harmonious attention network for person re-identification [C]// Proceedings of the 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Piscataway: IEEE, 2018: 2285-2294. 10.1109/cvpr.2018.00243 |
16 | LI S, BAK S, CARR P, et al. Diversity regularized spatiotemporal attention for video-based person re-identification [C]// Proceedings of the 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Piscataway: IEEE, 2018: 369-378. 10.1109/cvpr.2018.00046 |
17 | LIU H, FENG J S, QI M B, et al. End-to-end comparative attention networks for person re-identification[J]. IEEE Transactions on Image Processing, 2017, 26(7): 3492-3506. 10.1109/tip.2017.2700762 |
18 | 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 |
19 | 刘紫燕,万培佩.基于注意力机制的行人重识别特征提取方法[J].计算机应用, 2020, 40(3): 672-676. |
LIU Z Y, WAN P P. Pedestrian re-identification feature extraction method based on attention mechanism[J]. Journal of Computer Applications, 2020, 40(3): 672-676. | |
20 | 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 |
21 | SCHUMANN A, STIEFELHAGEN R. Person re-identification by deep learning attribute-complementary information [C]// Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops. Piscataway: IEEE, 2017: 1435-1443. 10.1109/cvprw.2017.186 |
22 | TAY C P, ROY S, YAP K H. AANet: attribute attention network for person re-Identifications [C]// Proceedings of the 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Piscataway: IEEE, 2019: 7127-7136. 10.1109/cvpr.2019.00730 |
23 | SHEN Y T, LI H S, YI S, et al. Person re-identification with deep similarity-guided graph neural network [C]// Proceedings of the 2018 European Conference on Computer Vision, LNCS 11219. Cham: Springer, 2018: 508-526. |
24 | BAO L Q, MA B P, CHANG H, et al. Masked graph attention network for person re-identification [C]// Proceedings of the 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops. Piscataway: IEEE, 2019: 1496-1505. 10.1109/cvprw.2019.00191 |
25 | WANG G A, YANG S, LIU H Y, et al. High-order information matters: learning relation and topology for occluded person re-identification [C]// Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Piscataway: IEEE, 2020: 6448-6457. 10.1109/cvpr42600.2020.00648 |
26 | KIPF T N, WELLING M. Semi-supervised classification with graph convolutional networks[EB/OL]. (2017-02-22) [2022-03-22]. . 10.48550/arXiv.1609.02907 |
27 | CHEN Q Y, ZHANG W, FAN J P. Cluster-level feature alignment for person re-identification[EB/OL]. (2020-08-15) [2022-07-12]. . |
28 | YAO H T, XU C S. Dual cluster contrastive learning for object re-identification[EB/OL]. (2022-04-21) [2022-07-12]. . |
29 | ZHENG L, SHEN L Y, TIAN L, et al. Scalable person re-identification: a benchmark [C]// Proceedings of the 2015 IEEE International Conference on Computer Vision. Piscataway: IEEE, 2015: 1116-1124. 10.1109/iccv.2015.133 |
30 | RISTANI E, SOLERA F, ZOU R, et al. Performance measures and a data set for multi-target, multi-camera tracking [C]// Proceedings of the 2016 European Conference on Computer Vision, LNCS 9914. Cham: Springer, 2016: 17-35. |
31 | ROSENBLATT F. The perceptron: a probabilistic model for information storage and organization in the brain[J]. Psychological Review, 1958, 65(6): 386-408. 10.1037/h0042519 |
32 | JIA J, HUANG H J, YANG W J, et al. Rethinking of pedestrian attribute recognition: realistic datasets and a strong baseline[EB/OL]. (2020-05-26) [2022-03-24]. . |
33 | 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 |
34 | 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 |
35 | MIKOLOV T, SUTSKEVER I, CHEN K, et al. Distributed representations of words and phrases and their compositionality [C]// Proceedings of the 26th International Conference on Neural Information Processing Systems — Volume 2. Red Hook, NY: Curran Associates Inc., 2013: 3111-3119. |
36 | PENNINGTON J, SOCHER R, MANNING C D. GloVe: global vectors for word representation [C]// Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, PA: ACL, 2014: 1532-1543. 10.3115/v1/d14-1162 |
37 | ZHANG G H, LIANG G Y, SU F, et al. Cross-domain attribute representation based on convolutional neural network [C]// Proceedings of the 2018 International Conference on Intelligent Computing, LNCS 10956. Cham: Springer, 2018: 134-142. |
38 | XU S M, LUO L K, HU S Q. Attention-based model with attribute classification for cross-domain person re-identification [C]// Proceedings of the 25th International Conference on Pattern Recognition. Piscataway: IEEE, 2021: 9149-9155. 10.1109/icpr48806.2021.9413309 |
39 | XU B L, LIU J X, HOU X X, et al. Cross domain person re-identification with large scale attribute annotated datasets[J]. IEEE Access, 2019, 7: 21623-21634. 10.1109/access.2019.2896663 |
40 | XIAO Q Q, CAO K L, CHEN H N, et al. Cross domain knowledge transfer for person re-identification[EB/OL]. (2016-11-18) [2022-03-25]. . |
41 | LUO H, GU Y Z, LIAO X Y, et al. Bag of tricks and a strong baseline for deep person re-identification [C]// Proceedings of the 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops. Piscataway: IEEE, 2019: 1487-1495. 10.1109/cvprw.2019.00190 |
42 | WEN Y D, ZHANG K P, LI Z F, et al. A discriminative feature learning approach for deep face recognition [C]// Proceedings of the 2016 European Conference on Computer Vision, LNCS 9911. Cham: Springer, 2016: 499-515. |
43 | LI X Y, JIANG S Q. Know more say less: image captioning based on scene graphs[J]. IEEE Transactions on Multimedia, 2019, 21(8): 2117-2130. 10.1109/tmm.2019.2896516 |
[1] | Ying HUANG, Jiayu YANG, Jiahao JIN, Bangrui WAN. Siamese mixed information fusion algorithm for RGBT tracking [J]. Journal of Computer Applications, 2024, 44(9): 2878-2885. |
[2] | Jieru JIA, Jianchao YANG, Shuorui ZHANG, Tao YAN, Bin CHEN. Unsupervised person re-identification based on self-distilled vision Transformer [J]. Journal of Computer Applications, 2024, 44(9): 2893-2902. |
[3] | Rui ZHANG, Pengyun ZHANG, Meirong GAO. Self-optimized dual-modal multi-channel non-deep vestibular schwannoma recognition model [J]. Journal of Computer Applications, 2024, 44(9): 2975-2982. |
[4] | Cui WANG, Miaolei DENG, Dexian ZHANG, Lei LI, Xiaoyan YANG. Review of end-to-end person search algorithms based on images [J]. Journal of Computer Applications, 2024, 44(8): 2544-2550. |
[5] | Xun YAO, Zhongzheng QIN, Jie YANG. Generative label adversarial text classification model [J]. Journal of Computer Applications, 2024, 44(6): 1781-1785. |
[6] | Junfeng SHEN, Xingchen ZHOU, Can TANG. Dual-channel sentiment analysis model based on improved prompt learning method [J]. Journal of Computer Applications, 2024, 44(6): 1796-1806. |
[7] | Yuxiang LIN, Yunbing WU, Aiying YIN, Xiangwen LIAO. Multi-modal summarization model based on semantic relevance analysis [J]. Journal of Computer Applications, 2024, 44(1): 65-72. |
[8] | Yirui HUANG, Junwei LUO, Jingqiang CHEN. Multi-modal dialog reply retrieval based on contrast learning and GIF tag [J]. Journal of Computer Applications, 2024, 44(1): 32-38. |
[9] | Doudou LI, Wanggen LI, Yichun XIA, Yang SHU, Kun GAO. Skeleton-based action recognition based on feature interaction and adaptive fusion [J]. Journal of Computer Applications, 2023, 43(8): 2581-2587. |
[10] | Yubin GUO, Xiang WEN, Pan LIU, Ximing LI. Cross-modal person re-identification relation network based on dual-stream structure [J]. Journal of Computer Applications, 2023, 43(6): 1803-1810. |
[11] | Xiaoyu FAN, Suzhen LIN, Yanbo WANG, Feng LIU, Dawei LI. Reconstruction algorithm for highly undersampled magnetic resonance images based on residual graph convolutional neural network [J]. Journal of Computer Applications, 2023, 43(4): 1261-1268. |
[12] | Jie SUN, Shaoxin WU, Xuejun WANG, Jing HUA. Efficient person search algorithm and optimization with Sophon SC5+ chip architecture [J]. Journal of Computer Applications, 2023, 43(3): 744-751. |
[13] | Yingmao YAO, Xiaoyan JIANG. Video-based person re-identification method based on graph convolution network and self-attention graph pooling [J]. Journal of Computer Applications, 2023, 43(3): 728-735. |
[14] | Jianhua ZHONG, Chuangyi QIU, Jianshu CHAO, Ruicheng MING, Jianfeng ZHONG. Cloth-changing person re-identification model based on semantic-guided self-attention network [J]. Journal of Computer Applications, 2023, 43(12): 3719-3726. |
[15] | Meng DOU, Zhebin CHEN, Xin WANG, Jitao ZHOU, Yu YAO. Review of multi-modal medical image segmentation based on deep learning [J]. Journal of Computer Applications, 2023, 43(11): 3385-3395. |
Viewed | ||||||
Full text |
|
|||||
Abstract |
|
|||||