李玺教授

李玺,教授

IEEE&ACM Member

中国图形图像学会理事

CCF计算机视觉专委会委员

浙江省计算机学会计算机视觉专委会和多媒体专委会副主任委员

E-mail:xilizju@zju.edu.cn

Homepage: http://mypage.zju.edu.cn/xilics

 

现为浙江大学计算机学院全职教授,入选第五批中国国家青年千人计划和浙江省151人才工程培养第二层次。其在国际权威期刊和国际顶级学术会议发表文章约100篇,包括TPAMI(4篇)、IJCV(3篇)、TIP(6篇)、TNNLS(2篇)、TKDE(4篇)、TSMC(1篇)、TMM(1篇)、TCSVT(2篇)、ACM TIST(1篇)、PR(1篇)、IVC(1篇)、ICCV(5篇,1篇录用为Oral)、CVPR(5篇)、ECCV(1篇)、ICML(1篇,oral)、AAAI(2篇,1篇录用为Oral)、IJCAI(3篇)、ICDM(1篇,Oral)、ACM MM(6篇)、WWW(1篇)等。这些研究成果受到了国际学术界和工业界的关注,Google Scholar他引1700多次,SCI他引480多次,单篇SCI他引最高次数58,拥有一篇ESI高被引论文。担任神经计算领域知名国际刊物Neurocomputing和Neural Processing Letters的副主编,同时担任多个计算机视觉和模式识别方面的国际刊物和国际会议的审稿人和程序委员(如TPAMI、TIP、TCSVT、TMM、ICCV、CVPR等)。在2016年上海举行的中国计算机视觉研究与应用创新论坛(RACV)上做大会特邀报告。

申请人获得两项最佳国际会议论文奖(包括ACCV 2010和DICTA 2012),以及一项ICIP 2015 Top 10% 会议论文奖,另外分别获得两项中国北京市自然科学技术奖(包括一等奖和二等奖),获得2016 Microsoft Research Asia Collaborative Research Award,以及一项中国专利优秀奖。另外,带领学生团队进入2015年阿里巴巴大规模图像搜索大赛的决赛阶段,获得第6名(报名参赛队伍逾800多支)。所指导博士生在2012年取得了DICTA(数字图像计算技术及其应用国际会议)最佳论文奖。

申请人担任了多个国际著名的顶级学术会议的Program Committee Member(如CVPR2017、IJCAI2017、CVPR2016、ICCV 2015、ACM Multimedia 2015、BMVC2011等),同时参加众多国际著名的学术会议(如ICCV 2005、ICPR 2006、CVPR 2008、BMVC 2008、ICASSP 2009、ACCV 2010、ICCV 2011、CVPR 2012、DICTA 2012、ICCV 2013等),并作了一些大会口头报告(Oral Presentation)。在学术交流活动方面,申请人获聘成为中国计算机学会(CCF)计算机视觉专委会的委员,同时以特邀讲者的身份参与CCF走进大连理工大学的学术活动。

 

  • 承担的部分科研项目:
  1. 国家自然科学基金面上项目、61472353、基于自适应特征学习和表观建模的目标跟踪算法研究、2015/01-2018/12、在研、主持。
  2. 国家重点基础研究发展计划(973)课题二、2015CB352300、三元空间群智计算、2014/11 -2019/11、在研、排名第二。
  3. 国家自然科学基金-浙江两化融合联合基金、U1509206、城市智慧安监的相关基础理论和视觉分析技术、2016/01-2019/12、在研、排名第二。

 

  • 代表性论文及专著:
  1. He, Z., Li, X*., Zhang, Z., Wu, F., Geng, X., Zhang, Y., Yang, M., and Zhuang, Y., "Data-Dependent Label Distribution Learning for Age Estimation",IEEE Transactions on Image Processing (TIP), 2017.
  2. Wang, H.,Wu, F., Lu, W., Yang, Y., Li, X., Li, X., and Zhang, Y., "Identifying Objective and Subjective Words via Topic Modeling",IEEE Transactions on Neural Network and Learning Systems (TNNLS), 2017.
  3. Li, X., Zhao, L., Wei, L., Yang, M., Wu, F., Zhuang, Y., Ling, H., and Wang, J., "DeepSaliency: Multi-Task Deep Neural Network Model for Salient Object Detection",IEEE Transactions on Image Processing (TIP), 2016.
  4. Huang, S., Li, X*., Zhang, Z., He, Z., Wu, F., Liu, W., Tang, J., and Zhuang, Y., "Deep Learning Driven Visual Path Prediction from a Single Image",IEEE Transactions on Image Processing (TIP), 2016.
  5. Zhuang, Y., Song, J., Wu, F., Li, X., Zhang, Z., Rui, R., "Multi-modal Deep Embedding via Hierarchical Grounded Compositional Semantics," IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2016.
  6. Pi, T., Li, X*., Zhang, Z., Meng, D., Wu, F., Xiao, J., and Zhuang, Y., "Self-Paced Boost Learning for Classification", International Joint Conference on Artificial Intelligence (IJCAI), 2016.
  7. Zhang, Y., Li, X*., Zhao, L., and Zhang, Z., "Semantics-aware Deep Correspondence Structure Learning for Robust Person Re-identification", International Joint Conference on Artificial Intelligence (IJCAI), 2016.
  8. Wang, Z., Wu, F., Xiao, J., Li, X., Zhang, Z., and Zhuang, Y., Diversely Image Captioning via GroupTalk", International Joint Conference on Artificial Intelligence (IJCAI), 2016.
  9. Li, X., Pi, T., Zhao, X., Zhang, Z., Li, X., and Yu, P., "Learning Bregman Distance Functions for Structural Learning to Rank", IEEE Transactions on Knowledge and Data Engineering (TKDE), 2016.
  10. Wu, F., Wang, Z., Lu, W., Li, X., Yang, Y.,  Luo, J., and Zhuang Y.,  "Regularized Deep Belief Network for Image Attribute Detection", IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2016.
  11. Li, X., Shen, C., Dick, A., Zhang, Z., and Zhuang Y.,  "Online Metric-Weighted Linear Representations for Robust Visual Tracking", IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI),
  12. Li, X., Zhao, X., Zhang, Z., Wu, F., Zhuang, Y., and Wang, J., "Joint Multilabel Classification with Community-Aware Label Graph Learning",IEEE Transactions on Image Processing (TIP), 2015. 
  13. Li, P., Ling, H., Li, X., and Liao, C., "3D Hand Pose Estimation Using Randomized Decision Forest with Segmentation Index Points", Proceedings of International Conference on Computer Vision (ICCV), 2015.
  14. Yuan, C., Wu, B., Li, X.,Hu, W., Maybank, S., and Wang, F., “Fusing R Features and Local Features with Context-aware Kernels for Action Recognition,” International Journal of Computer Vision (IJCV),
  15. Zhao, X., Li, X*., Zhang, Z., Shen, C., Zhuang Y., Gao, L., and Li, X.,  “Scalable Linear Visual Feature Learning Via Online Parallel Nonnegative Matrix Factorization,” IEEE Transactions on Neural Network and Learning Systems (TNNLS) , 2015.
  16. Zhao, X, Li, X*., and Zhang, Z., “Joint Structural Learning To Rank With Deep Linear Feature Learning,” IEEE Transactions on Knowledge and Data Engineering (TKDE), 2015.
  17. Zhou, X., Li, X*., and Hu, W.,  “Learning A Superpixel-Driven Speed Function for Level Set Tracking,"  IEEE Transactions on Cybernetics, 2015.
  18. Fang, H., Wu, F., Li, X., Tang, S., Lu, W., Yang, Y., Zhu, W., and Zhuang, Y.,  “Aspect learning for multimedia summarization via non-parametric Bayesian," IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2015.
  19. Tan, X., Wu, F., Li, X., Tang, S., Lu, W., and Zhuang, Y., “Structured Visual Feature Learning for Classification via Supervised Probabilistic Tensor Factorization ,” IEEE Transactions on Multimedia (TMM), 2015. 
  20. Wu, F., Jiang X., Li, X., Tang, S., Lu, W., Zhang, Z., and Zhuang, Y., “Cross-Modal Learning to Rank via Latent Joint Representation,” IEEE Transactions on Image Processing (TIP), 2015. 
  21. Jiang, X., Wu, F., Li, X., Zhao, Z., Lu, W., Tang, S., and Zhuang, Y., "Deep Compositional Cross-modal Learning to Rank via Local-Global Alignment," Proceedings of ACM International Conference on Multimedia (ACM MM), 2015.
  22. Zhao, L., Li, X*., Xiao, J., Wu, F., and Zhuang, Y., “Metric Learning-Driven Multi-Task Structured Output Optimization for Robust Keypoint Tracking,” Proceedings of Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI), 2015. (Oral Presentation)
  23. Wu, F., Song J., Yang, Y., Li, X., Zhang, Z., and Zhuang, Y., “Structured embedding via pairwise relations and long-range interactions,” Proceedings of Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI), 2015.
  24. Pi, T., Li, X*., and Zhang, Z., “Structural Bregman Distance Functions Learning to Rank with Self-Reinforcement,” Proceedings of IEEE International Conference on Data Mining (ICDM), 2014.
  25. Wang, F., Wu, F., Song, J., Li, X., and Zhuang, Y., “Multi-modal Mutual Topic Reinforce Modeling for cross-media retrieval,” Proceedings of ACM International Conference on Multimedia (ACM MM), 2014.
  26. Lu, X., Wu, F., Li, X., Zhang, Y., Lu, W., Wang, D., and Zhuang, Y., “Learning Multimodal Neural Network with Ranking Examples,” Proceedings of ACM International Conference on Multimedia (ACM MM), 2014.
  27. Wang, H., Wu, F., Li, X., Tang S., and Zhuang, Y., “Jointly Discovering Fine-grained and Coarse-grained Sentiments via Topic Modeling,” Proceedings of ACM International Conference on Multimedia (ACM MM),
  28. Li, X., Hu, W., Shen, C., Dick, A., and Zhang, Z., “Context-aware hypergraph construction for robust spectral clustering”, IEEE Transactions on Knowledge and Data Engineering(TKDE), DOI: 10.1109/TKDE.2013.126, 2013.
  29. Li, X., Hu, W., Shen, C., Dick, A., Zhang, Z., and Hengel, A.v.d., “A survey of appearance models in visual object tracking”,ACM Transactions on Intelligent Systems and Technology(TIST), 4(4), pp.1-58, 2013. (ESI高被引论文)
  30. Li, X., Dick, A., Shen, C., Hengel, A.v.d., and Wang, H., “Incremental learning of 3D-DCT compact representations for robust visual tracking”, IEEE Transactions on Pattern Analysis and Machine Intelligence(TPAMI), 35(4):863-881, 2013.
  31. Li, X., Dick, A., Shen, C., Zhang, Z., Hengel, A.v.d., and Wang, H., “Visual tracking with spatio-temporal Dempster-Shafer information fusion”, IEEE Transactions on Image Processing(TIP), 22(8), 3028-3040, 2013.
  32. Hu, W., Tian, G., Li, X.*, and Maybank, S.,“An improved hierarchical dirichlet process-hidden markov model and its application to trajectory modeling and retrieval”,International Journal of Computer Vision (IJCV), 105(3), pp. 246-268, 2013.
  33. Yuan, C., Li, X., Hu, W., Ling, H., and Maybank, S., “Modeling geometric-temporal context with directional pyramid co-occurrence for action recognition”, IEEE Transactions on Image Processing(TIP), 23(2), pp.658-672, 2013.
  34. Hu, W., Li, X.*, Tian, G., Maybank, S., and Zhang, Z., “An incremental DPMM-based method for trajectory clustering, modeling and retrieval”, IEEE Transactions on Pattern Analysis and Machine Intelligence(TPAMI), 35(5), pp. 1051-1065, 2013.
  35. Hu, W., Li, X.*, Luo, W., Zhang, X., Maybank, S., and Zhang, Z., “Single and multiple object tracking using log-euclidean riemannian subspace and block-division appearance model”, IEEE Transactions on Pattern Analysis and Machine Intelligence(TPAMI), 34(12), pp.2420-2440, 2012.
  36. Hu, W., Li, X.*, Zhang, X., Shi, X., Maybank, S., and Zhang, Z., "Incremental Tensor Subspace Learning and Its Applications to Foreground Segmentation and Tracking", International Journal of Computer Vision(IJCV), Vol. 91, No. 3, pages 303-327, 2010.
  37. Chen, Y., Dick, A., Li, X*, and Hengel, A.v.d., “Spatially aware feature selection and weighting for object retrieval”, Image and Vision Computing (IVC), 31(12), pp. 935-948, 2013.
  38. Chen, Y., Li, X.*, Dick, A., and Hill, R., “Ranking consistency for image matching and object retrieval”, Pattern Recognition (PR), 47(3), pp. 1349-1360 2014.
  39. Li, X., Li, Y., Shen, C., Dick, A., and Hengel, A.v.d., “Contextual hypergraph modeling for salient object detection”, Proceedings of International Conference on Computer Vision(ICCV), 2013.
  40. Li, X., Lin, G., Shen, C., Hengel, A.v.d., and Dick A., “Learning hash functions using column generation”, Proceedings of International Conference on Machine Learning(ICML), 2013.
  41. Li, X., Shen, C., Dick, A., and Hengel, A.v.d., “Learning compact binary codes for visual tracking”, Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition(CVPR), 2013.
  42. Yuan, C., Li, X., Hu, W., Ling, H., and Maybank, S., “3D R-transform on spatio-temporal interest points for action recognition”, Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition(CVPR), 2013.
  43. Li, X., Shen, C., Shi, Q., Dick, A., and Hengel, A.v.d., “Non-sparse linear representations for visual tracking with online reservoir metric learning”, Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition(CVPR), 2012.
  44. Li, X., Dick, A., Wang, H., Shen, C., and Hengel, A.v.d., “Graph mode-based contextual kernels for robust SVM tracking”, Proceedings of IEEE International Conference on Computer Vision(ICCV), 2011.
  45. Sahbi, H. and Li, X., “Context Based Support Vector Machines for Interconnected Image Annotation”, Proceedings of Asian Conference on Computer Vision (ACCV), 2010. (Oral Presentation, Best Paper Award)
  46. Sahbi, H. and Li, X., “Context Dependent SVMs for Interconnected Image Network Annotation”, Proceedings ofACM International Conference on Multimedia (ACM MM), 2010.
  47. Li, X., Hu, W., Zhang, Z., and Zhang X., “Robust visual tracking based on an effective appearance model”, Proceedings ofEuropean Conference on Computer Vision (ECCV), 2008.
  48. Li, X., Hu, W., Zhang, Z., and Zhang X., Zhu, M., and Chen J., “Visual tracking via incremental Log-Euclidean Riemannian subspace learning”, Proceedings ofIEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2008. 
  49. Li, X., Hu, W., Zhang, Z., and Zhang X., “Robust visual tracking based on incremental tensor subspace learning”, Proceedings of IEEE International Conference on Computer Vision (ICCV), 2007.
  50. Zhu, M., Hu, W., and Li, X., “Customizable Instance-Driven Webpage Filtering Based on Semi-Supervised Learning”, Proceedings of IEEE/WIC/ACM International Conference on Web Intelligence (WI), 2007.
  51. Zhu, M., Hu, W., Wu, O., Li, X., and Zhang, X., “User Oriented Link Function Classification”, Proceedings ofInternational World Wide Web Conference (WWW), 2008.
  52. Zhang, X., Hu, W., Maybank, S., and Li, X., “Graph based discriminative learning for robust and efficient object tracking”, Proceedings of IEEE International Conference on Computer Vision (ICCV), 2007.(Oral presentation)
  53. Zhang, X., Hu, W., Maybank, S., and Li, X., “Sequential particle swarm optimization for visual tracking”, Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), 2008.

  

  • 发明专利:
  1. 基于频谱特征分析的图像重复检测方法, 发明专利, 中国, 2009.7,CN 200710304207.8
  2. 一种可个性化定制的网页过滤方法, 发明专利, 中国, 2009.7,CN 200710304224.1
  3. 一种高效的敏感图像检测方法及其系统, 发明专利, 中国, 2010.6,CN 200810240942.1
  4. 一种图像型垃圾邮件的过滤方法, 发明专利, 中国, 2009.9,CN 200810100949.3
  5. 一种基于多模态隐性耦合表达的跨媒体排序方法,发明专利,中国,2,CN201410593006.4
  6. 一种基于主题模型的跨模态检索方法,发明专利,中国,1,CN201410532057.6
  7. 一种信息检索方法及系统,发明专利,中国,2,CN201410733635.2
  8. 一种静态场景中的实时运动目标提取方法,发明专利,中国,2015.4,CN201410727997.0