About

  • I am a Research Scientist at Hikvision Research America and currently looking for interns! Please contact me if you are interested in working on frontier computer vision and machine learning problems. 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.

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. 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)

  • 2. 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

  • 3. 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)

  • 4. 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)

  • 5. 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)

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

  • 7. 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

  • 8. 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

  • 9. 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

  • 10. 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.)

  • 11. 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)

  • 12. 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)

  • 13. 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

  • 14. 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

  • 15. 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.

  • 16. *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.

  • 17. *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

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

  • 19. *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

  • 20. *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.

  • 21. *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