王涛

博士、教授

基本信息

办公电话：51688566 电子邮件： twang@bjtu.edu.cn
通讯地址：北京交通大学计算机学院九教北525 邮编：100044

教育背景

2013年1月，北京交通大学  计算机科学与技术专业    博士学位

2004年4月，北京交通大学  计算机应用技术专业       硕士学位

2001年7月，北京交通大学  计算机科学与技术专业    学士学位


工作经历


2021.12至今，北京交通大学计算机学院          教授

2020.12至今，北京交通大学计算机学院          科学系教师党支部书记

2016.12-2021.11，北京交通大学计算机学院    副教授

2014.12-2015.12，美国天普大学计算机系       访问学者

2006.12-2016.11，北京交通大学计算机学院    讲师

2004.04-2006.11，北京交通大学计算机学院    助教


研究方向

  • 机器学习与认知计算
  • 计算机技术
  • 软件工程
  • 人工智能
  • 大数据技术与工程
  • 数字媒体信息处理与智能分析
  • 新一代电子信息技术

招生专业

  • 计算机科学与技术硕士
  • 计算机技术硕士
  • 软件工程硕士
  • 人工智能硕士
  • 大数据技术与工程硕士
  • 计算机科学与技术博士
  • 新一代电子信息技术（含量子技术等）硕士
  • 软件工程博士
  • 新一代电子信息技术（含量子技术等）博士
  • 人工智能博士
  • 计算机技术博士

科研项目

  1. 国家自然科学基金"面上项目"：可信赖异质图神经网络研究，2024-01-01--2027-12-31，主持

  2. 国家自然科学基金"面上项目"：面向关系推理的图神经网络关键问题研究，2021-01-01--2024-12-31，主持

  3. 国家自然科学基金"面上项目"：基于多模态超图的社群图像检索研究，2017-01-01--2020-12-31，主持

  4. 国家自然科学基金"青年项目"：基于组合地图模型的图像检索算法研究，2014-01-01--2016-12-31，主持

  5. 北京市自然科学基金“面上项目”：面向关系推理的深度神经网络模型及算法研究，2020-01-01--2022-12-31，主持

  6. 国家级"科技委"：XXXX系统构建与计算推演算法，2022-05-01--2023-06-30，主持

  7. 国家级平台专项：面向移动通信网络的大图数据分析与挖掘算法研究，2022-04-01--2020-03-30，主持

  8. 横向课题：交通产业元宇宙技术与应用发展趋势研究，2024-05-01--2024-12-31，主持

  9. 横向课题：视频监控智能分析技术，2016-05-01--2016-12-31，主持

  10. 基本科研业务费：面向AR的高精度目标跟踪技术研究，2018-04-01--2020-03-30，主持

  11. 基本科研业务费：基于内容安全的视频分析技术，2015-01-01--2016-12-31，主持

  12. 基本科研业务费：基于组合地图的图像匹配与检索算法研究，2012-03-01--2014-02-28，主持

  13. 国家级"科技委"：基于XXXX数据计算理论与方法，2022-08-29--2027-08-31，参加

  14. 国家级"科技委"：高动态微光战场环境下的目标感知与认知一体化技术研究，2020-08-01--2022-07-31，参加

  15. 国家（工信部等）专项：自动驾驶模拟仿真平台，2021-07-01--2023-06-30，参加

  16. 国家（工信部等）专项：工业互联网创新发展工程-工业企业侧安全数据采集设备，2019-08-01--2021-07-31，参加

  17. 国家重点研发计划-课题：异构交通主体群体智能协同行为仿真分析与评估，2019-03-01--2021-12-31，参加

  18. 国家重点研发计划-任务：社区基础数据采集、处理、应用、共享技术，2018-07-01--2021-06-30，参加

教学工作

本科课程：《面向对象程序设计与C++》。

研究生课程：《机器视觉基础》。

论文/期刊

Google Scholar:

https://scholar.google.com/citations?user=F3C5oAcAAAAJ&hl=zh-CN


2023:

[1] F Luo, J Wu, T Wang. Discrete Listwise Content-aware Recommendation. ACM Transactions on Knowledge Discovery from Data, 2023.

[2] H Liu, T Wang, Y Li, C Lang, Y Jin, H Ling. Joint graph learning and matching for semantic feature correspondence. Pattern Recognition, 2023.

[3] Z Xu, L Wei, C Lang, S Feng, T Wang, AG Bors, H Liu. SSR-Net: A Spatial Structural Relation Network for Vehicle Re-identification. ACM Transactions on Multimedia Computing, Communications and Applications, 2023.
[4] K Li, H Liu, T Wang. Centroid-based graph matching networks for planar object tracking. Machine Vision and Applications, 2023.

[5] H Liu, X You, T Wang, Y Li. Object detection via inner-inter relational reasoning network. Image and Vision Computing, 2023.


2022:

[1] G Zhao, T Wang, Y Li, Y Jin, C Lang, S Feng. Neighborhood Pattern Is Crucial for Graph Convolutional Networks Performing Node Classification. IEEE Transactions on Neural Networks and Learning Systems, 2022.

[2] F Luo, J Wu, T Wang. Discrete Listwise Personalized Ranking for Fast Top-N Recommendation with Implicit Feedback. IJCAI, 2022.

[3] XT You, H Liu, T Wang, S Feng, C Lang. Object detection by crossing relational reasoning based on graph neural network. Machine Vision and Applications. 2022.

[4] T Liang, Y Jin, W Liu, S Feng, T Wang, Y Li. Keypoint-Guided Modality-Invariant Discriminative Learning for Visible-Infrared Person Re-identification. ACM MM, 2022.

[5] Z Zhang, Y Jin, S Feng, Y Li, T Wang, H Tian. FENet: An Efficient Feature Excitation Network for Video-based Human Action Recognition. ICSP, 2022.

[6] X Li, T Liang, Y Jin, T Wang, Y Li. Camera-Aware Style Separation and Contrastive Learning for Unsupervised Person Re-Identification. ICME, 2022.

[7] X Deng, S Feng, G Lyu, T Wang, C Lang. Beyond word embeddings: Heterogeneous prior knowledge driven multi-label image classification. IEEE Transactions on Multimedia, 2022.

[8] L Wei, C Lang, L Liang, S Feng, T Wang, S Chen. Weakly supervised video object segmentation via dual-attention cross-branch fusion. ACM Transactions on Intelligent Systems and Technology , 2022.


2021:

[1] Z Li, C Lang, T Wang, Y Li, J Feng. Deep spatio-frequency saliency detection. Neurocomputing, 2021, 453:645-655.

[2] G Lyu, S Feng, Y Jin, T Wang, C Lang, Y Li. Prior Knowledge Regularized Self-Representation Model for Partial Multilabel Learning. IEEE Transactions on Cybernetics, 2021.

[3] G Zhao, T Wang, Y Li, C Lang. Entropy-aware Self-training for Graph Convolutional Networks. Neurocomputing, 2021.

[4] Z Xu, L Wei, C Lang, S Feng, T Wang, AG Bors. HSS-GCN: A Hierarchical Spatial Structural Graph Convolutional Network for Vehicle Re-identification. ICPR, 2021.

[5] M Wang, C Lang, L Liang, G Lyu, S Feng, T Wang. Class-balanced Text to Image Synthesis with Attentive Generative Adversarial Network. IEEE MultiMedia, 2021.

[6] M Wang, C Lang, S Feng, T Wang, Y Jin, Y Li. Text to photo-realistic image synthesis via chained deep recurrent generative adversarial network. Journal of Visual Communication and Image Representation, 2021.


2020:

[1] T Wang, H Liu, Y Li, Y Jin, H Ling*. Learning Combinatorial Solver for Graph Matching. CVPR, 2020. (oral)

[2] G Lyu, S Feng, T Wang, C Lang. A Self-Paced Regularization Framework for Partial-Label Learning. IEEE Transactions on Cybernetics, 2020.

[3] M Wang, C Lang, L Liang, S Feng, T Wang, Y Gao. End-to-End Text-to-Image Synthesis with Spatial Constrains. ACM Transactions on Intelligent Systems and Technology (TIST), 2020, 11(4):1-19.

[4] M Wang, C Lang, L Liang, G Lyu, S Feng, T Wang. Attentive Generative Adversarial Network To Bridge Multi-Domain Gap For Image Synthesis. ICME, 2020, pp. 1-6.

[5] Z Li, Y Jin, Y Li, C Lang, S Feng, T Wang. Learning part-alignment feature for person re-identification with spatial-temporal-based re-ranking method. World Wide Web, 23(3):1907-1923.

[6] Y Li, K Liu, Y Jin, T Wang, W Lin. VARID: Viewpoint-aware re-identification of vehicle based on triplet loss. IEEE Transactions on Intelligent Transportation Systems. 2020.

[7] T Liang, Y Jin, Y Li, T Wang. EDCNN: Edge enhancement-based Densely Connected Network with Compound Loss for Low-Dose CT Denoising. ICSP, 2020.


2019:

[1] T Wang, H Ling*, C Lang and S Feng. Deformable Surface Tracking by Graph Matching. ICCV, 2019.

[2] L Sun, S Feng, T Wang, C Lang and Y Jin.  Partial Multi-Label Learning by Low-Rank and Sparse Decomposition.  AAAI, 2019.

[3] G Lyu, S Feng, T Wang*, C Lang, Y Li. GM-PLL: Graph Matching based Partial Label Learning. IEEE Trans. on KDE, 2019. (online avaliable)

[4] Z Li, C Lang, J Feng, Y Li, T Wang, S Feng. Co-saliency Detection with Graph Matching, ACM Trans. on TIST, 10(3): 22-30. 2019.

[5] M Yin, C Lang, Z Li, S Feng, T Wang. Recurrent convolutional network for video-based smoke detection, Multimedia Tools and Applications, 78(1):237-256, 2019.

[6] C Qian, Y Jin, Y Li, C Lang, S Feng, T Wang. Deep Domain Adaptation for Asian Face Recognition via Ada-IBN. ICMEW, 2019.

[7] Z Li, Y Jin, Y Li, C Lang, S Feng, T Wang. Learning part-alignment feature for person re-identification with spatial-temporal-based re-ranking method. WWW, 2019.

[8] J Zhou, T Wang, Y Jin. The hypergraph matching based on CCRP.  BESC, 2019.


2018:

[1] T Wang, H Ling*. Gracker: A Graph-based Planar Object Tracker. IEEE Trans. on PAMI. 40(6):1494-1501, 2018.

[2] T Wang, H Ling*, C Lang and S Feng. Branching and Adaptive Path Following for Graph Matching. IEEE Trans. on PAMI.  40(12):2853-2867, 2018.

[3] T Wang, H Ling*, C Lang and S Feng. Constrained confidence matching for planar object tracking. ICRA, 2018. 

[4] J Zhou, T Wang*, C Lang, S Feng, Y Jin.  A novel hypergraph matching algorithm based on tensor refining. Journal of Visual Communication and Image Representation, 57:69-75, 2018. 

[5] S Xu, T Wang*, C Lang, S Feng, Y Jin. Graph-based visual odometry for VSLAM. Industrial Robot: An International Journal, 45(5):679-687, 2018. 

[6] Z Li, C Lang, S Feng, T Wang. Saliency ranker: A new salient object detection method. Journal of Visual Communication and Image Representation, 50:16-26, 2018. 

[7] D Xu, C Lang, S Feng, T Wang. A framework with a multi-task CNN model joint with a re-ranking method for vehicle re-identification. ICIMCS, 2018.

[8] K Yu, C Lang, S Feng, T Wang. Reasonably assign label distributions to GAN images in person re-identification baseline. BigMM, 2018. 

[9] X Xu, Y Li, Y Jin, C Lang, S Feng, T Wang. Hierarchical Discriminant Feature Learning for Heterogeneous Face Recoginition. VCIP, 2018.


2017:

[1] S Feng, C Lang, J Feng, T Wang, J Luo. Human facial age estimation by cost-sensitive label ranking and trace norm regularization, IEEE Transactions on Multimedia, 19(1):136-148, 2017.

[2] R Chen, C Lang, T Wang*. Multiple path exploration for graph matching, Machine Vision and Applications, 28(7): 695-703, 2017.

[3] Y Chen, T Wang*. Recursive formulas for embedding distributions of cubic outerplanar graphs, Australasian Journal of Combinatorics, 68(1):131-146, 2017.


2016:

[1] Tao Wang*, Haibin Ling, Congyan Lang, Jun Wu. Branching path following for graph matching. ECCV, 2016.

[2] Tao Wang*, Haibin Ling. Path following with adaptive path estimation for graph matching. AAAI, 2016.

[3] Tao Wang*, Haibin Ling, Congyan Lang, Songhe Feng. Symmetry-aware graph matching. Pattern Recognition, 60: 657-668, 2016.

[4] Zhu Teng, Tao Wang, Feng Liu, et al., From samples selection to model update: A robust online visual tracking algorithm against. Neurocomputing. 173: 1221-1234, 2016.


Earlier:

[1]. Tao Wang*, Guojun Dai, Bingbing Ni, D. Xu. A distance measure between labeled combinatorial maps. Computer Vision and Image Understanding. 116(6): 1168-1177, 2012.

[2]. Tao Wang*, Hua Yang, Congyan Lang, S. Feng. An error-tolerant approximate matching algorithm for labeled combinatorial maps. Neurocomputing. 156: 211-220, 2015. 

[3]. Tao Wang*, Guojun Dai, De Xu. A polynomial algorithm for submap isomorphism of general maps. Pattern Recognition Letters. 32(8): 1100-1107, 2011.

[4]. Tao Wang*, Yanpei Liu. Implements of some new algorithms for combinatorial maps. OR Transactions. 12(2): 58-66, 2008.

[5]. Tao Wang*, Congyan Lang, Songhe Feng. Joint tree of combinatorial maps. PAKDD 2014.

[6]. Tao Wang*, Weisheng Li. Fast low-cost shortest path tree algorithm. Journal of Software. 15(2): 660-665, 2004.

[7]. Tao Wang*, Weisheng Li. Shortest path subgraph. Journal of Northern Jiaotong University. 28(2):46-49, 2004.

[8]. Yichao Chen, Yanpei Liu, Tao Wang. The Total Embedding Distributions of Cacti and Necklaces. Acta Mathematica Sinica, English Series. Vol. 22, no. 5, pp. 1583-1590, 2006.

[9]. Shu Liu, Weisheng Li, Tao Wang. Advanced algorithm for fast lower-cost shortest path tree. Journal of Electronics and Information Technology. Vol. 27, no. 4, pp. 638-641, 2005.

 


专著/译著

专利

软件著作权

获奖与荣誉

2023年，PAAP 2023最佳学生论文奖

2022年，北京交通大学“智瑾奖教金优秀青年教师”

2020年，中国计算学会科技进步二等奖

2017年，北京交通大学“握奇奖教金优秀青年教师”

社会兼职


中国指挥与控制学会理事

中国图象图形学会交通视频专业委员会委员

CVPR、ICCV、ECCV、ICLR、AAAI、IJCAI等国际会议程序委员会委员

IEEE TPAMI、TMM、TIP、PR等期刊审稿人