About

  • I am a Senior Research Scientist at Hikvision Research America. Before joining Hikvision, I was a Staff Research Associate and Postdoctoral Researcher in the Center for Vision, Cognition, Learning, and Autonomy (VCLA) at University of California, Los Angeles (UCLA), under the supervision of Prof. Song-Chun Zhu, from 2016 to 2017. Before that, I received my Ph.D degree in Statistics at UCLA, under the supervision of Prof. Ying Nian Wu in 2016. I received double M.S. degree in Statistics and Cmputer Science at UCLA in 2014 and 2012 respectively. Before joining UCLA, I received my B.E. degree in Software Engineering from Jinan University, China in 2008. My primary research interest lies in statistical modeling, computing and learning. In particular, I am interested in generative models and unsupervised learning. I am looking for prospective interns and collaborators. Please contact me if you are interested in working on frontier computer vision and machine learning problems.

Education

  • 2004-2008
  • Jinan University, Guangzhou, China
  • Bachelor of Engineering in Software Engineering, 2008

Research Interests

  • Statistical Modeling and Computing, Machine Learning, Computer Vision, and Artificial Intelligence

Selected Papers

  • 1. Cooperative Learning of Descriptor and Generator Networks [project page]
  • --Jianwen Xie, Yang Lu, Ruiqi Gao, Song-Chun Zhu, Ying Nian Wu
  • --IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI ) 2018 (under review)

  • 2. Learning Descriptor Networks for 3D Shape Synthesis and Analysis [PDF][project page]
  • --Jianwen Xie *, Zilong Zheng *, Ruiqi Gao, Wenguan Wang, Song-Chun Zhu, Ying Nian Wu (* equal contributions)
  • --IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2018 (Oral)

  • 3. A Causal And-Or Graph Model for Visibility Fluent Reasoning in Tracking Interacting Objects [PDF]
  • --Yuanlu Xu *, Lei Qin *, Xiaobai Liu, Jianwen Xie, Song-Chun Zhu (* equal contributions)
  • --IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2018

  • 4. Weakly and Semi Supervised Human Body Part Parsing via Pose-Guided Knowledge Transfer [PDF]
  • --Hao-Shu Fang, Guansong Lu, Xiaolin Fang, Jianwen Xie, Yu-Wing Tai, Cewu Lu
  • --IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2018 (Spotlight)

  • 5. Cooperative Learning of Energy-Based Model and Latent Variable Model via MCMC Teaching [PDF][project page]
  • --Jianwen Xie, Yang Lu, Ruiqi Gao, Ying Nian Wu
  • --The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI) 2018 (Oral)

  • 6. Sparse and Deep Generalizations of the FRAME Model [PDF][Tex]
  • --Ying Nian Wu, Jianwen Xie, Yang Lu, Song-Chun Zhu
  • --Annals of Mathematical Sciences and Applications (AMSA) 2018
  • (an invited paper to the AMSA special issue in honor of Professor David Mumford on his 80th birthday)

  • 7. Super-Trajectory for Video Segmentation [PDF]
  • --Wenguan Wang, Jianbing Shen, Jianwen Xie, Fatih Porikli
  • --International Conference on Computer Vision (ICCV) 2017

  • 8. Synthesizing Dynamic Pattern by Spatial-Temporal Generative ConvNet [PDF][project page]
  • --Jianwen Xie, Song-Chun Zhu, Ying Nian Wu
  • --IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017

  • 9. Generative Hierarchical Learning of Sparse FRAME Models [PDF][project page]
  • --Jianwen Xie, Yifei Xu, Erik Nijkamp, Ying Nian Wu, Song-Chun Zhu
  • --IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017

  • 10. Decoding the Encoding of Functional Brain Networks: an fMRI Classification Comparison of Non-negative Matrix Factorization (NMF), Independent Component Analysis (ICA), and Sparse Coding Algorithms [PDF]
  • --Jianwen Xie, Pamela K. Douglas, Ying Nian Wu, Arthur L. Brody, Ariana E. Anderson
  • --Journal of Neuroscience Methods 2017

  • 11. A Theory of Generative ConvNet [PDF]
  • --Jianwen Xie *, Yang Lu *, Song-Chun Zhu, Ying Nian Wu (* equal contributions)
  • (an expanded version of the ICML-16 paper written for statisticians.)

  • 12. A Theory of Generative ConvNet [PDF][project page]
  • --Jianwen Xie *, Yang Lu *, Song-Chun Zhu, Ying Nian Wu (* equal contributions)
  • --International Conference on Machine Learning (ICML) 2016 (Oral)

  • 13. Inducing Wavelets into Random Fields via Generative Boosting [PDF][project page]
  • --Jianwen Xie, Yang Lu, Song-Chun Zhu, Ying Nian Wu
  • --Journal of Applied and Computational Harmonic Analysis (ACHA) 2015
  • (ACHA is a premier journal in harmonic analysis and applied mathematics)

  • 14. Learning Sparse FRAME Models for Natural Image Patterns [PDF][project page]
  • --Jianwen Xie, Wenze Hu, Song-Chun Zhu, Ying Nian Wu
  • --International Journal of Computer Vision (IJCV) 2014

  • 15. Learning Inhomogeneous FRAME Models for Object Patterns [PDF][project page]
  • --Jianwen Xie, Wenze Hu, Song-Chun Zhu, Ying Nian Wu
  • --IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2014

  • 16. Non-negative Matrix Factorization of Multimodal MRI, fMRI and Phenotypic Data reveals Differential Changes in Default Mode Subnetworks in ADHD [PDF]
  • --A. Anderson, P.K. Douglas , W.T. Kerr, V.S. Haynes, A.L. Yuille, Jianwen Xie, Ying Nian Wu, M.S. Cohen
  • --NeuroImage 2014.

    • * The following are early papers published when I was an undergraduate student.

  • 17. *Linear Programming with Fuzzy Relation Constraints: A Molecular-Diffusion Based Particle Swarm Optimization Approach
  • --Jianwen Xie, Xiaoxiang Liu, Weigang Jiang
  • --International Conference on Artificial Intelligence (ICAI) 2009.

  • 18. *Feature Selection Algorithm based on Association Rules (in Chinese)
  • 基于关联规则的特征选择算法
  • --Jianhua Wu, Qinbao Song, Junyi Shen, Jianwen Xie
  • --Pattern Recognition and Artificial Intelligence (模式识别与人工智能) 2009

  • 19. *Feature Selection Algorithm based on Association Rules Mining Method
  • --Jianwen Xie, Jianhua Wu, Qingquan Qian
  • --International Conference on Computer and Information Science (ICIS) 2009

  • 20. *Railway Freight Volume Forecasting Based on Unbiased Grey-Fuzzy-Markov Chain Method (in Chinese)
  • 基于无偏灰色模糊马尔可夫链法的铁路货运量预测研究
  • --Jianwen Xie, Yuanbiao Zhang, and Zhiwei Wang
  • --Journal of the China Railway Society (铁道学报) 2009

  • 21. *An Improved Grey-Markov Chain Method with an Application to Predict the Number of Chinese International Airlines
  • --Jianwen Xie, Yuanbiao Zhang, Weigang Jiang
  • --International Symposium on Information Science and Engineering (ISISE) 2008.

  • 22. *A K-means Clustering Algorithm with Meliorated Initial Centers and Its Application to Partition of Diet Structures
  • --Jianwen Xie, Yuanbiao Zhang, and Weigang Jiang
  • --International Symposium on Intelligent Information Technology Application Workshops (IITAW) 2008.

Honors

  • 2015 Dissertation Year Fellowship, UCLA
  • 2012 University Fellowship, UCLA
  • 2008 Distinguished Graduate of Class 2008, Jinan University
  • 2008 Outstanding Undergraduate Thesis, Jinan University
  • 2008 Outstanding Students Scholarship, Jinan University
  • 2007 National Scholarship, Ministry of Education, China
  • 2006, 2007 First Prize of Excellent Students Scholarship, Jinan University
  • 2005, 2006 Second Prize of the President's Scholarship, Jinan University
  • 2005 Second Prize of Excellent Students Scholarship, Jinan University

Competition Awards

  • 2012 Outstanding Winner of Interdisciplinary Contest in Modeling (ICM), USA
  • 2009 Meritorious Winner of Mathematical Contest in Modeling (MCM), USA
  • 2008 Meritorious Winner of Interdisciplinary Contest in Modeling (ICM), USA
  • 2007 National 2rd Prize & Guangdong Provincial 1st Prize of China Undergraduate Mathematical Contest in Modeling (CUMCM)
  • 2007 First Prize of “Chinese Society for Electrical Engineering Cup” China Mathematical Contest in Modeling (EMCM

Professional Service

  • Conference Reviewer: NIPS 2016; CVPR 2017, 2018; ICCV 2017; ECCV 2018
  • Journal Reviewer: IEEE Transactions on Knowledge and Data Engineering, Human Brain Mapping