Wei Liu                                   刘威


Director of Computer Vision Group@Tencent AI Lab


Thesis supervisor: Professor Shih-Fu Chang

Email: wliu at 

Google Scholar Page   


Research interests: machine learning, data mining, information retrieval, and

computer vision. My PhD thesis is dedicated to large-scale machine learning algorithms 

for classification and search. Currently, I am working on combinatorial, parallel, and distributed optimization methods to tackle noise/outlier present, high-dimensional, and large-scale learning problems. I am particularly interested in developing binary coding

and hashing techniques to handle big data.


     Resume   Publications   Courses   Collaborators
















l        Our SIGIR’16 paper Discrete Collaborative Filtering wins the Best Paper Award Honorable Mention!

l        We give a tutorial of “Compact Features for Visual Search” at CVPR 2016.

l        Hashing by Deep Learning, which is a section of our hashing survey paper appearing in Proceedings of the IEEE 2015.

l        I act as a guest editor of  Neurocomputing Special Issue on Advanced Learning for Large-Scale Heterogeneous Computing 2016.

l        I am teaching the Computer Vision course at Stevens Institute of Technology in 2015 Spring.

l        I act as a guest editor of  ACM TIST Special Issue on Mobile Social Multimedia Analytics in the Big Data Era 2015.

l        One paper is accepted by KDD’15.

l        Four papers are accepted by CVPR’15, and two papers are accepted by ICCV’15.

l        Two papers are accepted by AAAI’15, and two papers are accepted by IJCAI’15.

l        I taught the Database Mining course at RPI in 2014 Fall.

l        Two papers were accepted by NIPS’14, and one is spotlight oral.

l        Two papers were accepted by CVPR’14 oral sessions.

l        One paper was accepted by ECCV’14, and one paper was accepted by AAAI’14.

l        One paper won the Best Paper Travel Award of IEEE International Symposium on Biomedical Imaging (ISBI), 2014.

l        Three papers were accepted by ICCV’13. Thanks to the support of Josef Raviv Memorial Postdoctoral Fellowship.

l        I acted as a guest editor of Neurocomputing Special Issue on Learning for 3D Understanding 2013.

l        I won Jury Award for best thesis of Department of Electrical Engineering, Columbia University, 2013.

l        I passed my PhD defense on August 24th, 2012.

l        I won Josef Raviv Memorial Postdoctoral Fellowship 2012-2013.

l        I was awarded Facebook Fellowship 2011-2012 (one of five winners worldwide). Thanks to Facebook!



Significant Publications


1.        Large-Scale Machine Learning for Classification and Search   Wei Liu. PhD Thesis 2012.

2.        Robust and Scalable Graph-Based Semisupervised Learning   Wei Liu et al. Proceedings of the IEEE 2012.

3.        Efficient Robust Conditional Random Fields   Dongjin Song, Wei Liu, Tianyi Zhou, Dacheng Tao, and David A. Meyer. IEEE TIP 2015. New!

4.        Towards Large-Scale Histopathological Image Analysis: Hashing-Based Image Retrieval  Xiaofan Zhang, Wei Liu, Murat Dundar, Sunil Badve, and Shaoting Zhang. IEEE TMI 2015.

5.        Video De-Fencing   Yadong Mu, Wei Liu, and Shuicheng Yan. IEEE TCSVT 2014.

6.        Semi-Supervised Distance Metric Learning for Collaborative Image Retrieval and Clustering   Steven C. H. Hoi, Wei Liu, and Shih-Fu Chang. TOMCCAP 2010

(a long version of CVPR 2008 with code therein).

7.        Zeta Hull Pursuits: Learning Nonconvex Data Hulls   Yuanjun Xiong, Wei Liu, Deli Zhao, and Xiaoou Tang. NIPS 2014.

8.        Discrete Graph Hashing   Wei Liu et al. NIPS 2014 (spotlight oral).

9.        Compact Hyperplane Hashing with Bilinear Functions   Wei Liu et al. ICML 2012 (oral).

10.     Hashing with Graphs   Wei Liu et al. ICML 2011 (oral). code

11.     Large Graph Construction for Scalable Semi-Supervised Learning   Wei Liu et al. ICML 2010 (oral). code

12.     Semi-Supervised Sparse Metric Learning Using Alternating Linearization Optimization   Wei Liu et al. KDD 2010 (full oral).

13.     Unsupervised One-Class Learning for Automatic Outlier Removal   Wei Liu et al. CVPR 2014 (oral).

14.     Supervised Hashing with Kernels   Wei Liu et al. CVPR 2012 (oral). code

15.     Noise Resistant Graph Ranking for Improved Web Image Search   Wei Liu et al. CVPR 2011.

16.     Robust Multi-Class Transductive Learning with Graphs   Wei Liu and Shih-Fu Chang. CVPR 2009. code

17.     Hallucinating Faces: TensorPatch Super-Resolution and Coupled Residue Compensation   Wei Liu et al. CVPR 2005 (oral).

18.     Semi-Supervised Distance Metric Learning for Collaborative Image Retrieval   Steven C. H. Hoi, Wei Liu, and Shih-Fu Chang. CVPR 2008. code

19.     A Face Annotation Framework with Partial Clustering and Interactive Labeling   Yuandong Tian, Wei Liu, Rong Xiao, Fang Wen, and Xiaoou Tang. CVPR 2007.

20.     Learning Distance Metrics with Contextual Constraints for Image Retrieval   Steven C.H. Hoi, Wei Liu, Michael R. Lyu, and Wei-Ying Ma. CVPR 2006.

21.     Nonparametric Subspace Analysis for Face Recognition   Zhifeng Li, Wei Liu, Dahua Lin, and Xiaoou Tang. CVPR 2005.

22.     Top Rank Supervised Binary Coding for Visual Search   Dongjin Song, Wei Liu, Rongrong Ji, David A. Meyer, and John R. Smith. ICCV 2015. New!

23.     Learning Binary Codes for Maximum Inner Product Search   Fumin Shen, Wei Liu, Shaoting Zhang, Yang Yang, and Heng Tao Shen. ICCV 2015. New!

24.     Face Recognition via Archetype Hull Ranking   Yuanjun Xiong, Wei Liu, Deli Zhao, and Xiaoou Tang. ICCV 2013.

25.     Learning Hash Codes with Listwise Supervision   Jun Wang, Wei Liu, Andy Sun, and Yu-Gang Jiang. ICCV 2013.

26.     Output Regularized Metric Learning with Side Information   Wei Liu et al. ECCV 2008.

27.     Spatio-temporal Embedding for Statistical Face Recognition from Video   Wei Liu et al. ECCV 2006.

28.     Low-Rank Similarity Metric Learning in High Dimensions   Wei Liu et al. AAAI 2015. New!

29.     Constrained Metric Learning via Distance Gap Maximization    Wei Liu et al. AAAI 2010.

30.     Spectral Kernel Learning for Semi-Supervised Classification    Wei Liu et al. IJCAI 2009.

31.     Bayesian Tensor Inference for Sketch-based Facial Photo Hallucination    Wei Liu et al. IJCAI 2007.





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