基本信息

胡卫明,男, 中国科学院自动化研究所模式识别国家重点实验室研究员、博士生导师、中国科学院大学岗位教授、视频内容安全研究团队负责人,国家杰出青年科学基金获得者(2008)、中组部万人计划科技创新领军人才入选者(2016)、科技部中青年科技创新领军人才入选者(2013)、人社部百千万人才工程国家级人选者(2015)、国家有突出贡献中青年专家(2015)、享受国务院政府特殊津贴(2016)、国家863重点专项项目首席专家(2011)。以第一完成人获国家自然科学奖二等奖(2020)。

电子邮件:wmhu@nlpr.ia.ac.cn
通信地址:北京海淀区中关村东路95号
邮政编码:100190

研究领域

视频运动分析(含智能视觉监控)、网络多媒体内容安全分析与识别

招生信息

招生专业
081104-模式识别与智能系统
081203-计算机应用技术 
招收模式识别与智能系统、计算机应用技术两个专业的硕士生和博士生 

招生方向
视频信息处理:运动目标的检测、跟踪与行为理解(含智能视觉监控)、基于运动特征分析的视频检索、视频数据挖掘等。 

网络信息安全分析与识别:网络多媒体有害内容的识别、网络入侵模式分析等。

教育背景

   
学历

1998.04—2000.03: 在北京大学计算机科学技术研究所(即北大方正技术研究院)博士后流动站,从事博士后研究工作。合作教师为王选院士。
学位

1995.03—1998.03: 在浙江大学计算机系攻读工学博士学位。指导教师为何志均教授。
出国学习工作

曾多次到美国哥伦比亚大学、伊利诺伊斯大学厄巴那-香槟分校、英国雷丁大学和伦敦大学Birkbeck学院、法国波尔多第三大学、澳大利亚Monash大学和卧龙岗大学以及新加坡国立大学做访问研究。

工作经历

19983月进入北京大学计算机科学技术研究所(即北大方正技术研究院)博士后流动站,从事博士后研究工作。
20004月起在中国科学院自动化研究所模式识别国家重点实验室工作

国家自然科学基金委员会第十二、十三届专家评审组成员、国际顶级刊物IEEE Transactions on Pattern Analysis and Machine Intelligence的Associate Editor、国际权威刊物IEEE Transactions on : Cybernetics的Associate Editor。

专利与奖励

        2004年以第二完成人获北京市科学技术奖(基础研究类)一等奖。2008年以第一完成人获北京市科学技术奖(基础研究类)二等奖。2012年以第一完成人获北京市科学技术奖(技术发明类)一等奖。2013年以第一完成人获北京市发明专利奖一等奖、以第一完成人获中国专利优秀奖。2015年以唯一完成人获吴文俊人工智能科学技术奖一等奖。2020年以第一完成人获国家自然科学奖二等奖。授权发明专利60余项。主持完成了国家某大型网络监管重点示范工程项目,负责完成的敏感图像和视频识别技术、兴奋剂宣传销售信息识别技术得到了实际应用,负责开发了网络多模态有害信息过滤系统,带领团队研发成功直播平台云审核系统、便携式手机特定视频检测装备、异质媒体监测系统产品、网络直播智能监控系统等技术与系统实际应用于一百余家企事业单位,已在实战发挥作用,取得了显著的经济效益和社会效益。7年作为软件工程师的软件系统开发经历,独立完成源代码20万行以上

科研项目

主持了国家自然科学基金重点项目、重大国际合作项目、通用联合基金重点支持项目、人工智能基础应急管理项目、国家杰出青年基金项目,国家863重点专项项目、目标导向类课题,国家重大研究专项课题,国防科技创新特区课题,国家242信息安全计划重点课题,中国科学院前沿科学重点研究项目、对外合作重点项目,北京市自然科学基金重点项目、海淀原始创新联合基金重点研究专题项目、小米创新联合基金重点研究专题项目、重点国际合作项目等四十余项科研项目。

出版信息

   已在PAMIIJCV等国际刊物、国内一级刊物以及ICCVECCVCVPR等重要国际学术会议上发表论文357篇,其中第一作者50篇。据不完全统计,从20041月到202110月,发表的论文被Google Schoolar他引35010篇次;单篇单篇Google Scholar他引最高次数3111篇次。授权发明专利69项。
    主要国际权威刊物与顶级国际会议论文:

1.      Weiming Hu, Qiang Wang, Li Zhang, Luca Bertinetto, and Philip H.S. Torr, “SiamMask: A framework for fast online object tracking and segmentation,” IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 45, no. 3, pp. 3072-3089, March 2023.

2.      Yufan Liu, Jiajiong Cao, Bing Li, Weiming Hu, and Stephen Maybank, “Learning to explore distillability and sparsability: a joint framework for model compression,” IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 45, no. 3, pp. 3378-3395, March 2023.

3.      Jin Gao, Yan Lu, Xiaojuan Qi, Yutong Kou, Bing Li, Liang Li, Shan Yu, and Weiming Hu (), “Recursive least-squares estimator-aided online learning for visual tracking,” IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2022, Accepted.

4.      Weiming Hu, Haowei Liu, Yang Du, Chunfeng Yuan, Bing Li, and Stephen Maybank, “Interaction-aware spatio-temporal pyramid attention networks for action classification,” IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 44, no. 10, pp. 7010-7028, October 2022.

5.      Jin Gao, Qiang Wang, Junliang Xing, Haibin Ling, Weiming Hu (), and Stephen Maybank “Tracking-by-fusion via Gaussian process regression extended to transfer learning,” IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 42, no. 4, pp.  939-955, April 2020.

6.      Weiming Hu, Guodong Tian, Yongxin Kang, Chunfeng Yuan, and Stephen Maybank, “Dual sticky hierarchical Dirichlet process hidden Markov model and its application to natural language description of motions,” IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 40, no. 10, pp. 2355-2373, Oct. 2018.

7.      Junliang Xing, Zhiheng Niu, Junshi Huang, Weiming Hu (), Xi Zhou, and Shuicheng Yan, “Towards robust and accurate multi-view and partially-occluded face alignment,” IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 40, no. 4, pp. 987-1001, 2018.

8.      Bing Li, Chunfeng Yuan, Weihua Xiong, Weiming Hu, Houwen Peng, Xinmiao Ding, and Steve Maybank, “Multi-view multi-instance learning based on joint sparse representation and multi-view dictionary learning,” IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 39, no. 12, pp. 2554-2560, 2017.

9.      Houwen Peng, Bing Li, Haibin Ling, Weiming Hu (), Weihua Xiong, and Stephen J. Maybank, “Salient object detection via structured matrix decomposition,” IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 39, no. 4, pp. 818-832, April 2017. (Featured paper)

10.   Weiming Hu, Jin Gao, Junliang Xing, Chao Zhang, and Stephen Maybank, “Semi-supervised tensor-based graph embedding learning and its application to visual discriminant tracking,” IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 39, no. 1, pp. 172-188, Jan. 2017.

11.   Weiming Hu, Wei Li, Xiaoqin Zhang, and Stephen Maybank, “Single and multiple object tracking using a multi-feature joint sparse representation,” IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 37, no. 4, pp. 816-833, April 2015.

12.   Guang Luo, Shuang Yang, Guodong Tian, Chunfeng Yuan, Weiming Hu (), and Stephen J. Maybank, “Learning human actions by combining global dynamics and local appearance,” IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 36, no. 12, pp. 2466-2482, Dec. 2014. (Featured paper)

13.   Weiming Hu, Nianhua Xie, Ruiguang Hu, Haibin Ling, Qiang Chen, Shuicheng Yan, and Stephen Maybank, “Bin ratio-based histogram distances and their application to image classification,” IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 36, no. 12, pp. 2338-2352, Dec. 2014.

14.   Weiming Hu, Xi Li, Guodong Tian, Stephen Maybank, and Zhongfei Zhang, “An incremental DPMM-based method for trajectory clustering, modeling, and retrieval,” IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 35, no. 5, pp. 1051-1065, May 2013.

15.   Weiming Hu, Xi Li, Wenhan Luo, Xiaoqin Zhang, Stephen Maybank, and Zongfeng Zhang, “Single and multiple object tracking using log-euclidean Riemannian subspace and block-division appearance model,” IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 34, no. 12, pp. 2420-2440, 2012.

16.   Weiming Hu, Ou Wu, Zhouyao Chen, Zhouyu Fu, and Steve Maybank, “Recognition of pornographic web pages by classifying texts and images,” IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 29, no. 6, pp. 1019-1034, 2007.

17.   Weiming Hu, Xuejuan Xiao, Zhouyu Fu, Dan Xie, Tieniu Tan, and Steve Maybank, “A system for learning statistical motion patterns,” IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 28, no. 9, pp. 1450-1464, September 2006.

18.   Weiming Hu, Min Hu, Xue Zhou, Tieniu Tan, Jianguang Lou, and Steve Maybank, “Principal axis-based correspondence between multiple cameras for people tracking,” IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 28, no. 4, pp. 663-671, April 2006.

19.   Liang Wang, Tieniu Tan, Huazhong Ning, and Weiming Hu, “Silhouette analysis based gait recognition for human identification,” IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol. 25, no. 12, pp. 1505-1518, 2003.

20.   Weiming Hu, Xinchu Shi, Zongwei Zhou, Junliang Xing, Haibin Ling, and Stephen Maybank, “Dual L1-normalized context aware tensor power iteration and its applications to multi-object tracking and multi-graph matching,” International Journal of Computer Vision (IJCV), vol. 128, no. 2, pp. 360-392, February 2020.

21.   Xinchu Shi, Haibin Ling, Yu Pang, Weiming Hu (), Peng Chu, and Junliang Xing, “Rank-1 tensor approximation for high-order association in multi-target tracking,” International Journal of Computer Vision (IJCV), vol. 127, no. 8, pp. 1063-1083, 2019.

22.  Chunfeng Yuan, Baoxin Wu, Xi Li, Weiming Hu (), Stephen Maybank, and Fangshi Wang, “Fusing R features and local features with context-aware kernels for action recognition,” International Journal of Computer Vision (IJCV), vol. 118, no. 2, pp. 151-171, June 2016.

23.  Bing Li, Weihua Xiong, Weiming Hu (), Brian Funt, and Junliang Xing, “Multi-cue illumination estimation via a tree-structured group joint sparse representation,” International Journal of Computer Vision (IJCV), vol. 117, no. 1, pp. 21-47, March 2016.

24.   Xiaoqin Zhang, Weiming Hu, Nianhua Xie, Hujun Bao, and Stephen Maybank, “A robust tracking system for low frame rate video,” International Journal of Computer Vision (IJCV), vol. 115, no. 3, pp. 279-304, December 2015.

25.  Weiming Hu, Guodong Tian, Xi Li, and Stephen Maybank, “An improved hierarchical Dirichlet process-hidden Markov model and its application to trajectory modeling and retrieval,” International Journal of Computer Vision (IJCV), vol. 105, no. 3, pp. 246-268, Dec. 2013.

26.   Weiming Hu, Xi Li, Xiaoqin Zhang, Xinchu Shi, Stephen Maybank, and Zhongfei Zhang, “Incremental tensor subspace learning and its applications to foreground segmentation and tracking,” International Journal of Computer Vision (IJCV), vol. 91, no. 3, pp. 303-327, February 2011.

27.   Ou Wu, Qiang You, Fen Xia, Lei Ma, and Weiming Hu, Listwise learning to rank from crowds,” ACM Transactions on Knowledge Discovery from Data (TKDD), vo. 11, no. 1, Article no. 4, 2016.

28.   Ou Wu, Weiming Hu, and Lei Shi, “Measuring the visual complexities of web pages,” ACM Transactions on the Web (TWEB), vol. 7, no. 1, Article no. 1, March 2013.

29.   Weiming Hu, Haiqiang Zuo, Ou Wu, Yunfei Chen, Zhongfei Zhang, and David Suter, “Recognition of adult images, videos, and web page bags,” ACM Transactions on Multimedia Computing, Communications and Applications. vol. 7S, 1, Article 28, October 2011.

30.   Ou Wu, Xue Mao, and Weiming Hu, “Iteratively divide-and-conquer learning for nonlinear classification and ranking,” ACM Transactions on Intelligent Systems and Technology (TIST), vol. 9, no. 2, Article no. 18:1-26, January 2018.

31.   Xi Li, Weiming Hu (), Chunhua Shen, Zhongfei Zhang, Anthony Dick, and Anton van den Hengel, “A survey of appearance models in visual object tracking,” ACM Transactions on Intelligent Systems and Technology, vol. 4, no. 4, Article no. 58, 2013.

32.   Weiming Hu, Jun Gao, Bing Li, Ou Wu, Junping Du, and Stephen Maybank, “Anomaly detection using local kernel density estimation and context-based regression,” IEEE Transactions on Knowledge and Data Engineering (KDE), vol. 32, no. 2, pp. 218-233, February 2020.

33.   Ou Wu, Qiang You, Xue Mao, Fen Xia, and Weiming Hu, “Listwise learning to rank by exploring structure of objects,” IEEE Transactions on Knowledge and Data Engineering (KDE), vol. 28, no. 7, pp. 1934-1939, 2016.

34.   Xi Li, Weiming Hu (), Chunhua Shen, Anthony Dick, and Zhongfei Mark Zhang, “Context-aware hypergraph construction for robust spectral clustering,” IEEE Transactions on Knowledge and Data Engineering (KDE), vol. 26, no. 10, pp. 2588-2597, October 2014.

35.   Shaoru Wang, Jin Gao, Bing Li, and Weiming Hu, “Narrowing the gap: improved detector training with noisy location annotations,” IEEE Transactions on Image Processing, vol. 31, pp. 6369-6380, 2022.

36.   Li Yang, Yan Xu, Shaoru Wang, Chunfeng Yuan, Ziqi Zhang, Bing Li, and Weiming Hu, “PDNet: Towards better one-stage object detection with prediction decoupling,” IEEE Transactions on Image Processing, vol. 31, pp. 5121-5133, 2022.

37.   Chao Liang, Zhipeng Zhang, Xue Zhou, Bing Li, Shuyuan Zhu, and Weiming Hu, “Rethinking the competition between detection and ReID in multiobject tracking,” IEEE Transactions on Image Processing, vol. 31, pp. 3182-3196, 2022.

38.   Zhipeng Zhang, Yufan Liu, Bing Li, Weiming Hu, and Houwen Peng, “Towards accurate pixelwise object tracking via attention retrieval,” IEEE Transactions on Image Processing, vol. 30, pp. 8553-8566, October 2021.

39.   Weiming Bai, Zhipeng Zhang; Bing Li, Pei Wang, Yangxi Li, Congxuan Zhang, and Weiming Hu, “Robust texture-aware computer-generated image forensic: benchmark and algorithm,” IEEE Transactions on Image Processing, vol. 30, pp. 8439-8453, 2021.

40.   Bo Wang, Chunfeng Yuan, Bing Li, Xinmiao Ding, Zeya Li, Ying Wu, and Weiming Hu, “Multi-scale low-discriminative feature reactivation for weakly supervised object localization,” IEEE Transactions on Image Processing, vol. 30, pp. 6050-6065, June 2021.

41.   Xinwei Huang, Bing Li, Shuai Li, Wenjuan Li, Weihua Xiong, Xuanwu Yin, Weiming Hu, and Hong Qin, “Multi-cue semi-supervised color constancy with limited training samples,” IEEE Transactions on Image Processing (TIP), vol. 29, pp. 7875-7888, 2020.

42.   Wenjuan Li, Bing Li, Chunfeng Yuan, Haohao Wu, Yangxi Li, Weiming Hu, and Fangshi Wang, “Anisotropic convolution for image classification,” IEEE Transactions on Image Processing (TIP), vol. 29, no. 1, pp. 5584-5595, December 2020.

43.   Hao Yang, Chunfeng Yuan, Li Zhang, Yunda Sun, Weiming Hu, Stephen J. Maybank, “STA-CNN: Convolutional spatial-temporal attention learning for action recognition,” IEEE Transactions on Image Processing (TIP), vol. 29, no. 1, pp. 5783-5793, December 2020.

44.   Guan Luo, Jiutong Wei, Weiming Hu, and Stephen J. Maybank, “Tangent Fisher vector on matrix manifolds for action recognition,” IEEE Transactions on Image Processing (TIP), vol. 29, no. 1, pp. 3052-3064, 2020.

45.   Weiming Hu, Baoxin Wu, Pei Wang, Chunfeng Yuan, Yangxi Li, and Stephen Maybank, “Context-dependent random walk graph kernels and tree pattern graph matching kernels with applications to action recognition,” IEEE Transactions on Image Processing (TIP), vol. 27, no. 10, pp. 5060-5075, October 2018.

46.   Weiming Hu, Yabo Fan, Junliang Xing, Liang Sun, Zhaoquan Cai, and Stephen Maybank, “Deep constrained siamese hash coding network and load-balanced locality-sensitive hashing for near duplicate image detection,” IEEE Transactions on Image Processing (TIP), vol. 27, no. 9, pp. 4452-4464, September 2018.

47.   Bing Li, Weihua Xiong, Ou Wu, Weiming Hu (), Stephen Maybank, and Shuicheng Yan, “Horror image recognition based on context-aware multi-instance learning,” IEEE Transactions on Image Processing (TIP), vol. 24, no. 12, pp. 5193-5205, 2015.

48.   Weiming Hu, Ruiguang Hu, Nianhua Xie, Haibin Ling, and Stephen Maybank, “Image classification using multi-scale information fusion based on saliency driven nonlinear diffusion filtering,” IEEE Transactions on Image Processing (TIP), vol. 23, no. 4, pp. 1513-1526, 2014.

49.   Chunfeng Yuan, Xi Li, Weiming Hu, Haibin Ling, and Stephen Maybank, “Modeling geometric-temporal context with directional pyramid co-occurrence for action recognition,” IEEE Transactions on Image Processing (TIP), vol. 23, no, 2, pp. 658-672, Feb. 2014.

50.   Bing Li, Weihua Xiong, Weiming Hu (), and Brian Funt, “Evaluating combinational illumination estimation methods on real-world images,” IEEE Transactions on Image Processing (TIP), vol. 23, no. 3, pp. 1194-1209, 2014.

51.   Haoran Wang, Chunfeng Yuan, Weiming Hu (), Haibin Ling, Changyin Sun, and Wankou Yang, “Action recognition using nonnegative action component representation and sparse basis selection,” IEEE Transactions on Image Processing (TIP), vol. 23, no. 2, pp. 570-581, Feb. 2014.

52.   Weiming Hu, Xue Zhou, Wei Li, Wenhan Luo, Xiaoqin Zhang, and Stephen Maybank, “Active contour-based visual tracking by integrating colors, shapes and motions,” IEEE Transactions on Image Processing (TIP), vol. 22, no. 5, pp. 1778-1792, May 2013.

53.   Weiming Hu, Dan Xie, Zhouyu Fu, Wenrong Zeng, and Steve Maybank, “Semantic-based surveillance video retrieval,” IEEE Transactions on Image Processing (TIP), vol. 16, no. 4, pp. 1168-1181, April 2007.

54.   Jianguang Lou, Tieniu Tan, Weiming Hu, Hao Yang, and Steve Maybank, “3-D model-based vehicle tracking,” IEEE Transactions on Image Processing (TIP), vol. 14, no. 10, pp. 1561-1569, 2005.

55.   Liang Wang, Tieniu Tan, Weiming Hu, and Huazhong Ning, “Automatic gait recognition based on statistical shape analysis,” IEEE Transactions on Image Processing (TIP), vol. 12, no. 9, pp. 1120-1131, 2003.

56.   Congxuan Zhang, Zhongkai Zhou, Zhen Chen, Weiming Hu, Ming Li, and Shaofeng Jiang, “Self-attention-based multiscale feature learning optical flow with occlusion feature map prediction,” IEEE Transactions on Multimedia (TMM), vol. 24, pp. 3340-3354, July 2022.

57.   Xinmiao Ding, Bing Li, Weihua Xiong, Wen Guo, Weiming Hu, and Bo Wang, “Multi-instance multi-label learning combining hierarchical context and its application to image annotation,” IEEE Transactions on Multimedia (TMM), vol. 18, no. 8, pp. 1616-1627, 2016.

58.   Ou Wu, Haiqiang Zuo, Weiming Hu, and Bing Li, “Multi-modal web aesthetics assessment based on structural SVM and multi-task fusion learning,” IEEE Transactions on Multimedia (TMM), vol. 18, no. 6, pp. 1062-1076, 2016.

59.   Weiming Hu, Xinmiao Ding, Bing Li, Jianchao Wang, Yan Gao, Fangshi Wang, and Stephen Maybank, “Multi-perspective cost-sensitive context-aware multi-instance sparse coding and its application to sensitive video recognition,” IEEE Transactions on Multimedia (TMM), vol. 18, no. 1, pp. 76-89, 2016.

60.   Xiaofeng Ruan, Yufan Liu, Chunfeng Yuan, Bing Li, Weiming Hu, Yangxi Li, and Stephen Maybank, “EDP: An efficient decomposition and pruning scheme for convolutional neural network compression,” IEEE Transactions on Neural Networks and Learning Systems(TNNLS), vol. 32, no. 10, pp. 4499-4513, Oct. 2021.

61.   Weiming Hu, Dan Xie, and Tieniu Tan, “A hierarchical self-organizing approach for learning the patterns of motion trajectories,” IEEE Transactions on Neural Networks, vol. 15, no. 1, pp. 135-144, 2004.

62.   Haowei Liu, Yongcheng Liu, Yuxin Chen, Chunfeng Yuan, Bing Li, and Weiming Hu, “TranSkeleton: Hierarchical spatial-temporal transformer for skeleton-based action recognition,” IEEE Transactions on Circuits and Systems for Video Technology, Accepted.

63.   Keyu Deng, Congxuan Zhang, Zhen Chen, Weiming Hu, Bing Li, and Feng Lu, “Jointing recurrent across-channel and spatial attention for multi-object tracking with block-erasing data augmentation,” IEEE Transactions on Circuits and Systems for Video Technology, Accepted.

64.   Zekun Li, Yufan Liu, Bing Li, Bailan Feng, Kebin Wu, Chengwei Peng, and Weiming Hu, “SDTP: Semantic-aware decoupled transformer pyramid for dense image prediction,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 32, no. 9, pp. 6160-6173, September 2022.

65.   Zhenbang Li, Yaya Shi, Jin Gao, Shaoru Wang, Bing Li, Pengpeng Liang, and Weiming Hu, “A simple and strong baseline for universal targeted attacks on siamese visual tracking”, IEEE Transactions on Circuits and Systems for Video Technology, vol. 32, no. 6, pp. 3880-3894, June 2022.

66.   Xinmiao Ding, Bing Li, Yangxi Li, Wen Guo, Yao Liu, Weihua Xiong, and Weiming Hu, “Web objectionable video recognition based on deep multi-instance learning with representative prototypes selection,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 31, no. 3, pp. 1222-1233, 2021.

67.   Junliang Xing, Weiming Hu, Haizhou Ai, and Shuicheng Yan, “FatRegion: A fast, adaptive, tree-structured region extraction approach,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 28, no. 3, pp. 601-615, 2018.

68.   Xiaoqin Zhang, Weiming Hu, Hujun Bao, and Steve Maybank, “Robust head tracking based on multiple cues fusion in the kernel-Bayesian framework,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 23, no. 7, pp. 1197-1208, 2013.

69.   Xiaoqin Zhang, Weiming Hu, Wei Qu, and Steve Maybank, “Multiple object tracking via species-based particle swarm optimization,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 20, no. 11, pp. 1590-1602, Nov. 2010.

70.   Weiming Hu, Xue Zhou, Min Hu, and Steve Maybank, “Occlusion reasoning for tracking multiple walking people,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 19, no. 1, pp. 114-121, 2009.

71.   Liang Wang, Huazhong Ning, Tieniu Tan, and Weiming Hu, “Fusion of static and dynamic body biometrics for gait recognition,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 14, no. 2, pp. 149-158, 2004.

72.   Weiming Hu, Jun Gao, Yanguo Wang, Ou Wu, and Stephen Maybank, “Online Adaboost-based parameterized methods for dynamic distributed network intrusion detection,” IEEE Transactions on Cybernetics, vol. 44, no. 1, pp. 66-82, 2014.

73.   Xue Zhou, Xi Li, and Weiming Hu, “Learning a superpixel-driven speed function for level set tracking,” IEEE Transactions on Cybernetics, vol. 46, no. 7, pp. 1498-1510, 2016.

74.   Ou Wu, Weiming Hu, Stephen J. Maybank, Mingliang Zhu, and Bing Li, “Efficient clustering aggregation based on data fragments,” IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, vol. 42, no. 3, pp. 913-926, 2012.

75.   Weiming Hu, Wei Hu, and Steve Maybank, “Adaboost-based algorithm for network intrusion detection,” IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, vol. 38, no. 2, pp. 577-583, 2008.

76.   Weiming Hu, Dan Xie, Tieniu Tan, and Steve Maybank, “Learning patterns of activity using fuzzy self-organizing neural network,” IEEE Transactions on Systems, Man and Cybernetics, Part B: Cybernetics, vol. 34, no. 3, pp. 1618-1626, 2004.

77.   Weiming Hu, Wei Hu, Nianhua Xie, and Steve Maybank, “Unsupervised active learning based on hierarchical graph-theoretic clustering,” IEEE Transactions on Systems, Man and Cybernetics, Part B: Cybernetics, vol. 39, no. 5, pp. 1147-1161, Oct. 2009.

78.   Weiming Hu, Tieniu Tan, Liang Wang, and Steve Maybank, “A survey on visual surveillance of object motion and behaviors,” IEEE Transactions on Systems, Man and Cybernetics, Part C: Applications and Reviews, vol. 34, no. 3, pp. 334-352, 2004.

79.   Weiming Hu, Nianhua Xie, Li Li, Xianglin Zeng, and Stephen Maybank, “A survey on visual content-based video indexing and retrieval,” IEEE Transactions on Systems, Man, and Cybernetics, Part C, Applications and Reviews, vol. 41, no. 6, pp. 797-819, 2011.

80.   Xiaoqin Zhang, Changcheng Li, Weiming Hu, Xiaofeng Tong, Steve Maybank, and Yimin Zhang, “Human pose estimation and tracking via parsing a tree structure based human model,” IEEE Transactions on Systems, Man and Cybernetics: Systems, vol. 44, no. 5, pp. 580-592, May 2014.

81.   Weiming Hu, Xuejuan Xiao, Dan Xie, Tieniu Tan, and Steve Maybank, “Traffic accident prediction using 3D model based vehicle tracking,” IEEE Transactions on Vehicular Technology, vol. 53, no. 3, pp. 677-694, 2004.

82.   Shuaiqi Liu, Siyuan Liu, Shichong Zhang, Bing Li, Weiming Hu, and Yu-Dong Zhan, “SSAU-Net: A Spectral-Spatial Attention-Based U-Net for Hyperspectral Image Fusion,” IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-16, 2022.

83.   Shuaiqi Liu, Yu Lei, Luyao Zhang, Bing Li, Weiming Hu, and Yu-Dong Zhang, “MRDDANet: A multiscale residual dense dual attention network for SAR image denoising,” IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-13, 2022.

84.   Yuxin Chen, Gaoqun Ma, Chunfeng Yuana, Bing Li, Hui Zhang, Fangshi Wang, and Weiming Hu, “Graph convolutional network with structure pooling and joint-wise channel attention for action recognition,” Pattern Recognition, vol. 103, pp. 107321: 1-13, July 2020.

85.   Zongwei Zhou, Wenhan Luo, QiangWang, Junliang Xing, and Weiming Hu, “Distractor- aware discrimination learning for online multiple object tracking,” Pattern Recognition, vol. 107, November 2020.

86.   Hao Yang, Chunfeng Yuan, Bing Li, Yang Du, JunliangXing, Weiming Hu, and Stephen J. Maybank, “Asymmetric 3D convolutional neural networks for action recognition,” Pattern Recognition, vol. 85, pp. 1-12, 2019.

87.   Kai Li, Junliang Xing, Weiming Hu, and Stephen J. Maybank, “D2C: Deep cumulatively and comparatively learning for human age estimation,” Pattern Recognition, vol. 66, pp. 95-105, 2017.

88.   Junliang Xing, Kai Li, Weiming Hu, Chunfeng Yuan, and Haibin Ling, “Diagnosing deep learning models for high accuracy age estimation from a single image,” Pattern Recognition, vol. 66, pp. 106-116, 2017.

89.   Xiaoqin Zhang, Wei Li, Weiming Hu, Haibin Ling, and Steve Maybank, “Block covariance based l1 tracker with a subtle template dictionary,” Pattern Recognition, 2013, vol. 46, no. 7, pp. 1750-1761, July 2013.

90.   Haoran Wang, Chunfeng Yuan, Weiming Hu (), and Changyin Sun, “Action recognition using linear dynamic systems,” Pattern Recognition, vol. 46, no. 6, pp. 1710-1718, 2013.

91.   Haoran Wang, Chunfeng Yuan, Weiming Hu (), and Changyin Sun, “Supervised class-specific dictionary learning for sparse modeling in action recognition,” Pattern Recognition, vol. 45, no. 11, pp. 3902-3911, 2012.

92.   Huazhong Ning, Tieniu Tan, Liang Wang, and Weiming Hu, “People tracking based on motion model and motion constraints with automatic initialization,” Pattern Recognition, vol. 37, no. 7, pp. 1423-1440, 2004.

93.   Liang Wang, Weiming Hu, and Tieniu Tan, “Recent developments in human motion analysis,” Pattern Recognition, vol. 36, no. 3, pp. 585-601, 2003.

94.   Zhipeng Zhang, Yihao Liu, Xiao Wang, Bing Li, and Weiming Hu, “Learn to match: automatic matching network design for visual tracking,” IEEE International Conference on Computer Vision (ICCV), pp. 13339-13348, 2021.

95.   Yuxin Chen, Ziqi Zhang, Chunfeng Yuan, Bing Li, Ying Deng, and Weiming Hu, “Channel-wise topology refinement graph convolution for skeleton-based action recognition,” IEEE International Conference on Computer Vision (ICCV), pp. 13359-13368, 2021.

96.   Xing Nie, Yongcheng Liu, Shaohong Chen, Jianlong Chang, Chunlei Huo, Gaofeng Meng, Qi Tian, Weiming Hu, and Chunhong Pan, “Differentiable convolution search for point cloud processing,” IEEE International Conference on Computer Vision (ICCV), pp. 7437-7446, 2021.

97.   Zhao Yang, Qiang Wang, Luca Bertinetto, Song Bai, Weiming Hu, and Philip H.S. Torr, “Anchor diffusion for unsupervised video object segmentation,” IEEE International Conference on Computer Vision (ICCV), pp. 931-940, 2019.

98.  Lin Ma, Xiaoqin Zhang, Weiming Hu, Junliang Xing, Jiwen Lu, and Jie Zhou, “Local subspace collaborative tracking,” IEEE International Conference on Computer Vision (ICCV), pp. 4301-4309, 2015.

99.   Junliang Xing, Jin Gao, Bing Li, Weiming Hu, and Shuicheng Yan, “Robust object tracking with online multi-lifespan dictionary learning,” IEEE International Conference on Computer Vision (ICCV), pp.665-672, 2013.

100.  Jin Gao, Junliang Xing, Weiming Hu, and Steve Maybank, “Discriminant tracking using tensor representation with semi-supervised improvement,” IEEE International Conference on Computer Vision (ICCV), pp. 145-152, 2013.

101.  Ou Wu, Weiming Hu, and Jun Gao, “Learning to predict the perceived visual quality of photos,” IEEE International Conference on Computer Vision (ICCV), pp. 225-232, 2011.

102.  Xiaoqin Zhang, Changcheng Li, Xiaofeng Tong, Weiming Hu, and Steve Maybank, “Efficient human pose estimation via parsing a tree structure based human model,” IEEE International Conference on Computer Vision (ICCV), pp. 1349-1356, 2009.

103.  Xi Li, Weiming Hu, and Zhongfei Zhang, “Robust visual tracking based on incremental tensor subspace learning,” IEEE International Conference on Computer Vision (ICCV), pp. 1-8, 2007.

104.  Xiaoqing Zhang, Weiming Hu, and Steve Maybank, “Graph based discriminative learning for robust and efficient object tracking,” IEEE International Conference on Computer Vision (ICCV), pp. 1-8, 2007.

105.  Liang Wang, Huazhong Ning, Tieniu Tan, and Weiming Hu, “Fusion of static and dynamic body biometrics for gait recognition,” IEEE International Conference on Computer Vision (ICCV), pp. 1449-1453, 2003.

106.  Li Yang, Yan Xu, Chunfeng Yuan, Wei Liu, Bing Li, and Weiming Hu, “Improving visual grounding with visual-linguistic verification and iterative reasoning,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 9489-9498, 2022.

107.  Zongyang Ma, Guan Luo, Jin Gao, Liang Li, Yuxin Chen, Shaoru Wang, Congxuan Zhang, and Weiming Hu, “Open-vocabulary one-stage detection with hierarchical visual-language knowledge distillation,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 14054-14063, 2022.

108.  Yaya Shi, Xu Yang, Haiyang Xu, Chunfeng Yuan, Bing Li, Weiming Hu, and Zheng-Jun Zha, “EMScore: Evaluating video captioning via coarse-grained and fine-grained embedding matching,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 17908-17917, 2022.

109.  Ziqi Zhang, Zhongang Qi, Chunfeng Yuan, Ying Shan, Bing Li, Ying Deng, and Weiming Hu, “Open-book video captioning with retrieve-copy-generate network,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 9837-9846, 2021.

110.  Jin Gao, Weiming Hu, and Yan Lu, “Recursive least-squares estimator-aided online learning for visual tracking,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 7386-7395, 2020.

111.  Ziqi Zhang, Yaya Shi, Chunfeng Yuan, Bing Li, PeijinWang, Weiming Hu, and Zhengjun Zha, “Object relational graph with teacher-recommended learning for video captioning,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 13278-13288, 2020.

112.  Qiang Wang, Li Zhang, Luca Bertinetto, Weiming Hu, and Philip H.S. Torr, “Fast online object tracking and segmentation: a unifying approach,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1328-1338, 2019.

113.  Yufan Liu, Jiajiong Cao, Bing Li, Chunfeng Yuan, Weiming Hu, Yangxi Li, Yunqiang Duan: “Knowledge distillation via instance relationship graph,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 7096-7104, 2019.

114.  Qiang Wang, Zhu Teng, Junliang Xing, Jin Gao, Weiming Hu, and Steve Maybank, “Learning attentions: residual attentional siamese network for high performance online visual tracking,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 4854-4863, 2018.

115.  Kai Li, Junliang Xing, Chi Su, Weiming Hu, Yundong Zhang, and Steve Maybank, “Deep cost-sensitive and order-preserving feature learning for cross-population age estimation,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 399-408, 2018.

116.  Yang Du, Chunfeng Yuan, Bing Li, Weiming Hu, and Stephen Maybank, “Spatio-temporal self-organizing map deep network for dynamic object detection from videos,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 4245-4254, 2017.

117.  Xinchu Shi, Haibin Ling, Weiming Hu, Junliang Xing, and Yanning Zhang, “Tensor power iteration for multi-graph matching,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 5062-5070, 2016.

118.  Shuang Yang, Chunfeng Yuan, Baoxin Wu, Weiming Hu, and Fangshi Wang, “Multi-feature max-margin hierarchical Bayesian model for action recognition,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1610-1618, 2015.

119.  Junliang Xing, Zhiheng Niu, Junshi Huang, Weiming Hu, and Shuicheng Yan, “Towards multi-view and partially-occluded face alignment,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.1829-1836, 2014.

120.  Xinchu Shi, Haibin Ling, Weiming Hu, Chunfeng Yuan, and Junliang Xing, “Multi-target tracking with motion context in tensor power iteration,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3518-3525, 2014.

121.  Baoxin Wu, Chunfeng Yuan, and Weiming Hu, “Human action recognition based on context-dependent graph kernels,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2609-2616, 2014.

122.  Chunfeng Yuan, Weiming Hu, Guodong Tian, and Shuang Yang, “Multi-task sparse learning with beta process prior for action recognition,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 423-429, 2013.

123.  Chunfeng Yuan, Xi Li, Weiming Hu, Haibin Lin, Stephen Maybank, and Haoran Wang, “3D R transform on spatio-temporal interest points for action recognition,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 724-730, 2013.

124.  Bing Li, Weihua Xiong, and Weiming Hu, “Illumination estimation based on bilayer sparse coding,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1423-1429, 2013.

125.  Xinchu Shi, Haibin Ling, Junliang Xing, and Weiming Hu, “Multi-target tracking by rank-1 tensor approximation,” IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2387-2394, 2013.

126.  Bing Li, Weihua Xiong, Weiming Hu, and Ou Wu, “Evaluating combinational color constancy methods on real-world images,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1929-1936, 2011.

127.  Nianhua Xie, Haibin Ling, Weiming Hu, and Xiaoqin Zhang, “Use bin-ratio information for category and scene classification,” IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2313-2319, 2010.

128.  Xi Li, Weiming Hu, Zhongfei Zhang, Xiaoqin Zhang, and Guan Luo, “Visual tracking via incremental log-Euclidean Riemannian subspace learning,” IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), Anchorage, Alaska. June 23-28, 2008.

129.  Xiaoqing Zhang, Weiming Hu, Steve Maybank, and Xi Li “Sequential particle swarm optimization for visual tracking,” IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), Anchorage, Alaska. June 23-28, 2008.

130.  Haina Qin, Longfei Han, Juan Wang, Congxuan Zhang, Yanwei Li, Bing Li, and Weiming Hu, “Attention-aware learning for hyperparameter prediction in image processing pipelines,” European Conference on Computer Vision (ECCV) vol. 19, pp. 271-287, 2022.

131.  Zhipeng Zhang, Houwen Peng, Jianlong Fu, Bing Li, and Weiming Hu, “Ocean: Object-aware anchor-free tracking,” European Conference on Computer Vision (ECCV), vol. 21, pp. 771-787, 2020.

132.  Yufan Liu, Minglang Qiao, Mai Xu, Bing Li, and Weiming Hu, and Ali Borji, “Learning to predict salient faces: a novel visual-audio saliency model,” European Conference on Computer Vision (ECCV), vol. 20, pp. 413-429, 2020.

133.  Yang Du, Chunfeng Yuan, Bing Li, Lili Zhao, Yangxi Li, and Weiming Hu, “Interaction-aware spatio-temporal pyramid attention networks for action classification,” European Conference on Computer Vision (ECCV), pp. 388-404, 2018.

134.  Mengdan Zhang, Qiang Wang, Junliang Xing, Jin Gao, Peixi Peng, Weiming Hu, and Steve Maybank, “Visual tracking via spatially aligned correlation filters network,” European Conference on Computer Vision (ECCV), vol. 3, pp. 484-500, 2018.

135.  Zheng Zhu, Qiang Wang, Bo Li, Wei Wu, Junjie Yan, and Weiming Hu, “Distractor-aware siamese networks for visual object tracking,” European Conference on Computer Vision (ECCV), 103-119, 2018.

136.  Pei Wang, Chunfeng Yuan, Weiming Hu, and Yanning Zhang, “Graph based skeleton motion representation and similarity measurement for action recognition,” European Conference on Computer Vision (ECCV), vol. 7, pp. 370-385, 2016.

137.  Jin Gao, Haibin Ling, Weiming Hu, and Junliang Xing, “Transfer learning based visual tracking with Gaussian processes regression,” European Conference on Computer Vision (ECCV), pp. 188-203, 2014.

138.  Houwen Peng, Bing Li, Weihua Xiong, Weiming Hu, and Rongrong Ji, “RGBD salient object detection: a benchmark and algorithms,” European Conference on Computer Vision (ECCV), pp. 92-109, 2014.

139.  Xi Li, Weiming Hu, Zhongfei Zhang, and Xiaoqin Zhang, “Robust visual tracking based on an effective appearance model,” European Conference on Computer Vision (ECCV), pp. 396-408, 2008.

140.  Mingzhe Guo, Zhipeng Zhang, Heng Fan, Liping Jing, Yilin Lyu, Bing Li, and Weiming Hu, “Learning target-aware representation for visual tracking via informative interactions,” International Joint Conference on Artificial Intelligence (IJCAI), pp. 927-934, 2022.

141.  Wenyang Luo, Yufan Liu, Bing Li, Weiming Hu, Yanan Miao, and Yangxi Li, “Long-short term cross-transformer in compressed domain for few-shot video classification,” International Joint Conference on Artificial Intelligence (IJCAI), pp. 1247-1253, 2022.

142.  Qiang Wang, Mengdan Zhang, Junliang Xing, Jin Gao, Weiming Hu, and Steve Maybank, “Do not lose the details: reinforced representation learning for high performance visual tracking,” International Joint Conference on Artificial Intelligence (IJCAI) pp. 985-991, 2018.

143.  Xue Mao, Zhouyu Fu, Ou Wu, and Weiming Hu, “Optimizing locally linear classifiers with supervised anchor point learning,” International Joint Conference on Artificial Intelligence (IJCAI), pp. 3699-3706, 2015.

144.  Ou Wu, Weiming Hu, and Jun Gao, “Learning to rank under multiple annotators,” International Joint Conference on Artificial Intelligence (IJCAI), pp. 1571-1576, 2011.

145.  Chao Liang, Zhipeng Zhang, Xue Zhou, Bing Li, and Weiming Hu, “One more check: making "fake background" be tracked again,” AAAI Conference on Artificial Intelligence (AAAI), pp. 1546-1554, 2022.

146.  Xiaofeng Ruan, Yufan Liu, Bing Li, Chunfeng Yuan, and Weiming Hu, “DPFPS: Dynamic and progressive filter pruning for compressing convolutional neural networks from scratch,” AAAI Conference on Artificial Intelligence (AAAI), pp. 2495-2503, 2021.

147.  Shaoru Wang, Yongchao Gong, Junling Xing, Lichao Huang, Chang Huang, and Weiming Hu, “RDSNet: A new deep architecture for reciprocal object detection and instance segmentation,” AAAI Conference on Artificial Intelligence (AAAI), pp. 12208-12215, 2020.

148.  Yang Du, Chunfeng Yuan, Bing Li, Weiming Hu, Hao Yang, Zhikang Fu, and Lili Zhao, “Hierarchical nonlinear orthogonal adaptive-subspace self-organizing map based feature extraction for human action recognition,” AAAI Conference on Artificial Intelligence (AAAI), pp. 6805-6812, 2018.

149.  Ou Wu, Ruiguang Hu, Xue Mao, and Weiming Hu, “Quality-based learning for web data classification,” AAAI Conference on Artificial Intelligence (AAAI), oral presentation, pp. 194-200, 2014.

150.  Qishen Wang, Ou Wu, Yin Chen, and Weiming Hu, “Label ranking by directly optimizing performance measure,” AAAI Conference on Artificial Intelligence (AAAI), pp. 131-133, 2013.

151. Houwen Peng, Bing Li, Rongrong Ji, and Weiming Hu, “Salient object detection via low-rank and structured sparse matrix decomposition,” AAAI Conference on Artificial Intelligence (AAAI), pp. 796-802, 2013.

152.  Bing Li, Weihua Xiong, and Weiming Hu, “Visual saliency map from tensor analysis,” AAAI Conference on Artificial Intelligence (AAAI), pp. 1585-1591, 2012.

153.  Mengdan Zhang, Jiashi Feng, Junliang Xing, and Weiming Hu, “Robust visual object tracking with top-down reasoning,” ACM Conference on Multimedia (ACM MM), pp. 226-234, 2017.

154.  Houwen Peng, Kai Li, Bing Li, Haibin Ling, Weihua Xiong, and Weiming Hu, “Predicting image memorability by multi-view adaptive regression,” ACM Conference on Multimedia (ACM MM), pp. 1147-1150, 2015.

155.  Bing Li, Weihua Xiong, and Weiming Hu, “Context-aware affective images classification based on bilayer sparse representation,” ACM Conference on Multimedia (ACM MM), pp. 721-724, 2012.

156.  Bing Li, Weihua Xiong, and Weiming Hu, “Scaring or pleasing: exploit emotional impact of an image,” ACM Conference on Multimedia (ACM MM), pp. 1365-1366, 2012 (Multimedia grand challenge).

科研活动

先后主持了国家自然科学基金重点项目、重大国际合作项目、通用联合基金重点支持项目、人工智能基础应急管理项目、国家杰出青年基金项目,国家863重点专项项目、目标导向类课题,国家242信息安全计划重点课题、中国科学院前沿科学重点研究项目、对外合作重点项目,北京市自然科学基金重点项目、海淀原始创新联合基金重点研究专题项目、重点国际合作项目等三十余项科研项目。

研究生培养情况

已培养出站博士后3名、毕业博士生18名、毕业硕士生17名。他们毕业后分别在国家著名研究机构、著名外资企业研究院工作或在国外有名的大学进一步深造。 指导的博士生王强获VOT2018视觉实时跟踪竞赛世界冠军。