LI Wen (李 文)

Ph.D.

Computer Vision Laboratory, ETH Zurich,
Sternwarstrasse 7, CH 8092, Zurich, Switzerland
  
Email: liwenbnu AT gmail DOT com
 
[CV][Google Scholar]


Biography

I am currently working with Prof. Luc Van Gool as a postdoctoral researcher at the Computer Vision Laboratory, ETH Zurich, Switzerland. 
Before this, I was a research associate in the Nanyang Technological University, Singapore, where I obtained my PhD degree under the supervision of Prof. Dong XU. I also worked closely with Prof. Ivor Wai-Hung Tsang during my PhD. I obtained my M.Eng. degree and B.S. degree from the Beijing Normal University, Beijing, China, on 2010 and 2007, respectively.

******New!!! Call for Participation!!! We are organizing CVPR 2017 Workshop on Visual Understanding by Learning from Web Data (WebVision 2017), an image classification challenge on 1,000 categories and a transfer learning images classification challenge are ongoing. Click to see more details!!!!


Research Interests

I am working on learning from weakly labeled web data and its applications in computer vision, which involves the following research topics,
  • Domain Adaptation: unsupervised domain adaptation, domain generalization, and heterogeneous domain adaptation.
  • Weakly Supervised Learning: multiple instance learning, semi-supervised learning, max-margin clustering and relative outlier detection.
  • Learning with Multiple Information: multi-view learning, learning using privileged information.
  • Multiple Kernel Learning: infinite kernel learning, and group-based multiple kernel learning.

Recent News
  • I released a fast implementation of kernel SVM+. Details of the algorithm can be found in our CVPR 2016 paper. The codes of linear SVM+ will also be released soon. Hope it would be helpful to your research. Visit my github for the software [codes].
  • I have one paper accepted by CVPR 2016.
  • I have one paper accepted by IJCV, collaborated with Li Niu (Sep 2015).
  • I have one paper accepted by ICCV 2015, collaborated with Li Niu (Sep 2015).
  • The extended version of Co-Labeling (ICDM 2012) has been accepted by T-PAMI, collaborated with Xinxing Xu (Aug 2015).
  • I have two papers accepted by CVPR 2015, collaborated with Li Niu and Shijie Xiao (Mar 2015).
  • I have uploaded the codes of our HFA algorithm, click here to download [codes] (Mar 2014). 
  • I added some useful resources on Multiple Instance Learning. Hope it will be useful if you would like to know about Multiple Instance Learning. Click here to view. (Nov 2012)

Selected Publications

Journal Papers
  1. Wen Li, Zheng Xu, Dong Xu, Dengxin Dai, and Luc Van Gool, “Domain Generalization and Adaptation using Low Rank Exemplar SVMs,” IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI).
  2. Yan Yan, Feiping Nie, Wen Li, Chenqiang Gao, Yi Yang, and Dong Xu, “Image Classification by Cross-Media Active Learning with Privileged Information,” IEEE Transactions on Multimedia (T-MM), vol. 18(12), pp. 2494-2502, Dec 2016.
  3. Li Niu, Wen Li, Dong Xu, and Jianfei Cai, “An Exemplar-Based Multi-View Domain Generalization Framework for Visual Recognition,” IEEE Transactions on Neural Networks and Learning Systems (T-NNLS).
  4. Li Niu, Wen Li, Dong Xu, and Jianfei Cai, “Visual Recognition by Learning from Web Data via Weakly Supervised Domain Generalization,” IEEE Transactions on Neural Networks and Learning Systems (T-NNLS).
  5. Li Niu, Wen Li, and Dong Xu, “Exploiting Privileged Information from Web Data for Action and Event Recognition,” International Journal of Computer Vision (IJCV), vol. 118(2), pp. 130-150, Jun 2016. 
  6. Wen Li*, Xinxing Xu*, Dong Xu, and Ivor Tsang, “Co-Labeling for Multi-view Weakly Labeled Learning,” IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), vol. 38(6), pp. 1113-1125, Jun 2016. (* contributed equally). 
  7. Xinxing Xu, Wen Li, Dong Xu, “Distance Metric Learning using Privileged Information for Face Verification and Person Re-identification ,” IEEE Transactions on Neural Networks and Learning Systems (T-NNLS), vol. 26(12), pp. 3150-3162, Dec 2015.
  8. Zhen Cui, Wen Li, Dong Xu, Shiguang Shan, Xilin Chen, and Xuelong Li, “Flowing on Riemannian Manifold: Domain Adaptation by Shifting Covariance,” IEEE Transactions on Systems, Man, and Cybernetics: Part B (T-SMC-B), vol. 44(12), pp. 2264-2273, Nov 2014.
  9. Wen Li, Lixin Duan, Dong Xu, and Ivor W.H. Tsang, “Learning with Augmented Features for Supervised and Semi-supervised Heterogeneous Domain Adaptation,” IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), vol. 36(6), pp. 1134-1148, JUN 2014. [Appendix][codes]
  10. Meina Kan, Dong Xu, Shiguang Shan, Wen Li and Xilin Chen, “ Learning Prototype Hyperplanes for Face Recognition in the Wild,” IEEE Transactions on Image Processing(T-IP), vol. 22(8), pp. 3310-3316, AUG 2013.
  11. Lixin Duan, Wen Li, Ivor W.H. Tsang  and Dong Xu, "Improving Web Image Search by Bag-based Re-ranking," IEEE Transactions on Image Processing (T-IP), vol. 20(11), pp. 3280-3290, NOV 2011. [BibTex]
Conference Papers
  1. Yuguang Yan*, Wen Li*, Michael Ng, Mingkui Tan, Hanrui Wu, Huaqing Min, and Qingyao Wu, "Learning Discriminative Correlation Subspace for Heterogeneous Domain Adaptation." International Joint Conference on Artificial Intelligence (IJCAI), 2017.
  2. Muhammad Ghifary, Bastiaan Kleijn, Mengjie Zhang, David Balduzzi, and Wen Li, “Deep Reconstruction-Classification Networks for Unsupervised Domain Adaptation,” European Conference on Computer Vision,(ECCV),2016 (spotlight paper).
  3. Wen Li, Dengxin Dai, Mingkui Tan, Dong Xu, and Luc Van Gool, “Fast Algorithms for Linear and Kernel SVM+,” IEEE International Conference on Computer Vision and Pattern Recognition(CVPR),2016. [Codes][errata]
  4. Li Niu, Wen Li, and Dong Xu, “Multi-view Domain Generalization for Visual Recognition,” IEEE International Conference on Computer Vision(ICCV), 2015.
  5. Li Niu, Wen Li, and Dong Xu, “Visual Recognition by Learning From Web Data: A Weakly Supervised Domain Generalization Approach,” IEEE International Conference on Computer Vision and Pattern Recognition(CVPR), pp. 2774-2783 , 2015.
  6. Shijie Xiao, Wen Li, Dong Xu, and Dacheng Tao, “FaLRR: A Fast Low Rank Representation Solver,” IEEE International Conference on Computer Vision and Pattern Recognition(CVPR), pp. 4612-4620, 2015.
  7. Zheng Xu, Wen Li, Li Niu, and Dong Xu, “Exploiting Low-rank Structure from Latent Domains for Domain Generalization,” European Conference on Computer Vision,(ECCV), pp. 628-643, 2014.
  8. Wen Li, Li Niu, and Dong Xu, “Exploiting Privileged Information from Web Data for Image Categorization,” European Conference on Computer Vision,(ECCV), pp. 437-452, 2014.
  9. Lin Chen, Wen Li, and Dong Xu, “Recognizing RGB Images by Learning from RGB-D Data,” IEEE International Conference on Computer Vision and Patter Recognition(CVPR), pp. 1418-1425, 2014.
  10. Huiying Liu, Dong Xu, Qingming Huang, Wen Li, Min Xu, and Stephen Lin, “Semantically-based Human Scanpath Estimation with HMMs,” IEEE International Conference on Computer Vision(ICCV), pp. 3232-3239, 2013. (Oral paper) [Slides]
  11. Hoang Anh Nguyen, and Wen Li, “Pose-Robust Representation for Face Verification in Unconstrained Videos,” IEEE International Conference on Image Processing(ICIP), pp. 3715-3719, 2013.
  12. Zhen Cui, Wen Li, Dong Xu, Shiguang Shan and Xilin Chen, “Fusing Robust Face Region Descriptors via Multiple Metric Learning for Face Recognition in the Wild,” IEEE International Conference on Computer Vision and Pattern Recognition(CVPR), pp. 3554-3561, 2013. [Codes][ROC_LFW, ROC_YTF]
  13. Wen Li, Lixin Duan, Ivor W.H. Tsang and  Dong Xu, “ Co-Labeling: A New Multi-View Learning Approach for Ambiguous Problems,” IEEE International Conference on Data Mning(ICDM), pp. 419-428, 2012. (full paper) [Slides][BibTex]
  14. Wen Li, Lixin Duan, Ivor W.H. Tsang and  Dong Xu, “ Batch Mode Adaptive Multiple Instance Learning for Computer Vision Tasks,” IEEE International Conference on Computer Vision and Pattern Recognition(CVPR), pp. 2368-2375, 2012.[BibTex]
  15. Wen Li, Lixin Duan, Dong Xu and Ivor W.H. Tsang, “Text-based Image Retrieval Using Progressive Multi-Instance Learning,” IEEE International Conference on Computer Vision(ICCV), pp. 2049-2055, 2011. [BibTex] [indices of relevant images]

Professional Service

Co-organizer of CVPR 2017 Workshop on Visual Understanding by Learning from Web Data.

Co-organizer of ECCV 2016 Workshop on Transferring and Adapting Source Knowledge (TASK) in Computer Vision (CV).

Co-organizer of ICDM 2015 Workshop on Practical Transfer Learning.

Conference Reviewer: ACM MM 2017, ICIP 2017, ICCV2017, CVPR2017, ECCV2016, ICIP2016, NIPS2015, IJCAI2015, ICIP2015, ICME2014, ICME2013, IJCAI2013, ACM-MM2013.

Journal Reviewer:
  • IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI)
  • International Journal of Computer Vision (IJCV)
  • Journal of Machine Learning Research (JMLR)
  • IEEE Transactions on Image Processing (T-IP)
  • IEEE Transactions on Information Forensics & Security (T-IFS)
  • IEEE Transactions on Neural Networks and Learning Systems (T-NNLS)
  • IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT)
  • IEEE Transactions on Systems, Man, and Cybernetics: Part B (T-SMC-B)
  • Computer Vision and Image Understanding (CVIU)
  • ACM Transactions on Multimedia Computing, Communications and Applications (ACM TOMM)
  • Pattern Recognition (PR)
  • Pattern Recognition Letters (PRL)
  • Machine Vision and Applications (MVAP)
  • Signal Processing (SP)


Teaching
  • Spring 2013: Engineering Mathematics, Nanyang Technological University, Teaching Assistant
  • Fall 2012: Discrete Mathematics, Nanyang Technological University, Teaching Assistant
  • Spring 2012: Data Structures, Nanyang Technological University, Teaching Assistant
  • Fall 2008: Data Mining, Beijing Normal University, Teaching Assistant
  • Spring 2008: Human Computer Interaction, School of Continuing Education, Beijing Normal University, Lecturer
  • Fall 2007: Mathematical Logic, Beijing Normal University, Teaching Assistant

Awards
  • 2016, ECCV Outstanding Reviewer Award.
  • 2014, Travel Grant for CVPR Doctoral Consortium 2014.
  • 2014, Travel Grant for Machine Learning Summer School 2014.
  • 2010-2014, NTU Research Scholarship.
  • 2010, Nanyang Engineering Doctoral Scholarship.
  • 2009, Head Award (for excellent intern) at SONY China Research Lab (院长奖).
  • 2010, Excellent Postgraduates of Beijing Normal University (北京师范大学优秀毕业生).
  • 2007, Excellent Graduates of Beijing (北京市优秀毕业生).