Xinchao Wang




Assistant Professor
Department of Computer Science
Stevens Institute of Technology

xinchao.wang-at-stevens.edu

Hoboken, New Jersey 07030



Simplicity is the final achievement. --- Frederic Chopin

Multiple PhD studentships available at the Stevens Institute of Technology, on the topics of Computer Vision and Machine Learning. Please contact me if you are interested.

News 


Press

I contributed to the prototype of some commercial software being deployed by NBA and covered by various media outlets.


Biography

I am currently a tenure-track assistant professor in the Dept. of Computer Science, Stevens Institute of Technology. Before joining Stevens, I was a Postdoc at Prof. Thomas Huang's Image Formation and Professing (IFP) group at Beckman Institute, University of Illinois Urbana-Champaign (UIUC). I received my Ph.D. from the Computer Vision Lab, École polytechnique fédérale de Lausanne (EPFL), advised by Prof. Pascal Fua, and the first-class honorable B.Sc. in Dept. of Computing, the Hong Kong Polytechnic University (HKPU) in 2010, advised by Prof. Zhu Li and Prof. Dacheng Tao.
 
My research interests include Computer Vision, Multimedia, Machine Learning, and Big Data Analytics.

[Google Scholar] [DBLP]


Education 
  • Ph.D., Computer Science, École polytechnique fédérale de Lausanne (EPFL)
    July 2015
    Supervisor: Prof. Pascal Fua
  • B.Sc. (Hon.), Computing, the Hong Kong Polytechnic University (HKPU)
    November 2010
    Supervisor: Prof. Zhu Li and Prof. Dacheng Tao

Oral Presentations
  • [CVPR 2017] by me, Spotlight Oral presentation on compressing DNNs. (acceptance rate = 8.0%)
  • [CVPR 2016] by my collaborator Andrii Maksai, Spotlight Oral presentations on tracking the ball in team sports. (acceptance rate = 9.6%)
  • [ECCV 2014] by me, Oral presentation on tracking interacting objects. (acceptance rate = 2.6%)

Code
  • Wide Activation and Weight Normalization for Image Super-Resolution (Winner of CVPR 2018 NTIRE) [Link]
  • Tracking Dividing Cells (TMI 2017) [Link]
  • Tracking Multiple Targets with Global Motions (ICCV 2017) [Link]
  • Batch-based Tracking (TIP 2017) [Link]
  • Two-Stage Residual Networks for Image Super Resolution (CVPR 2017 NTIRE) [Link]
  • Anti-Sparse Hashing (BMVC 2017) [Link]
  • Traffic Object Detection (AI City Challenge 2017) [Link]
  • GRP-DSOD Detector (ArXiv 2017) [Link]
  • Tracking Ball in Team Sports (CVPR 2016) [Link]
  • Intertwined Flows (TPAMI 2016) [Link]
  • Tracking Interacting Objects (ECCV 2014) [Link]

Teaching   
  • CS 559, Machine Learning Fundamentals and Applications, Spring 2018, Stevens Institute of Technology

Service   
  • Senior Program Committee:
    • AAAI Conference on Artificial Intelligence (AAAI), 2019
  • Associate Editor:
    • Journal of Visual Communication and Image Representation (JVCI)
  • Program Committee: 
    • Conference on Computer Vision and Pattern Recognition (CVPR), 2017, 2018
    • European Conference on Computer (ECCV), 2018
    • International Joint Conference on Artificial Intelligence (IJCAI), 2017, 2018 
    • ACM Multimedia (MM), 2017, 2018
    • AAAI Conference on Artificial Intelligence (AAAI), 2017
  • Journal Reviewer: 
    • IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
    • IEEE Transactions on Image Processing (TIP) 
    • IEEE Transactions on Medical Imaging (TMI)
    • Medical Image Analysis (MIA)
    • IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
    • Computer Vision and Image Understanding (CVIU)
    • ACM Transactions on Knowledge Discovery from Data (TKDD)

Selected Publications

X. Wang, E. Türetken, F. Fleuret and P. Fua, "Tracking Interacting Objects Using Intertwined Flows",  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2016. [PDF] [Project] [Code] [Datasets]

X. Wang, B. Fan, S. Chang, Z. Wang, X. Liu, D. Tao and T. Huang, "Greedy Batch-based Minimum-cost Flows for Tracking Multiple Objects", IEEE Transactions on Image Processing (TIP), 2017. [PDF] [Code]

X. Wang*, E. Türetken*, C. Becker, C. Haubold and P. Fua, "Network Flow Integer Programming to Track Elliptical Cells in Time-Lapse Sequences", IEEE Transactions on Medical Imaging (TMI), 2017. [PDF] [Project] [Code]


D. Liu, Z. Wang, Y. Fan, X. Liu, Z. Wang, S. Chang, X. Wang, and T. Huang, "Learning Temporal Dynamics for Video Super-Resolution: A Deep Learning Approach", IEEE Transactions on Image Processing (TIP), 2018. [PDF]


L. Lan, X. Wang, S. Zhang, D. Tao, W. Gao, and T. Huang, "Interacting Tracklets for Multi-object Tracking", IEEE Transactions on Image Processing (TIP), 2018. [PDF]

 
X. Yin, X. Wang, J. Yu, M. Zhang, P. Fua, and D. Tao, 
"FishEyeRecNet: A Multi-Context Collaborative Deep Network for Fisheye Image Rectification", European Conference on Computer Vision (ECCV), 2018. [PDF] [Code]

C. Zhou, C. Ding, Z. Lu X. Wang, and D. Tao, "One-pass Multi-task Convolutional Neural Networks for Efficient Brain Tumor Segmentation", Medical Image Computing & Computer Assisted Intervention (MICCAI), 2018 [PDF]




F. Wang, L. Zhao, X. Li, X. Wang, and D. Tao, "Geometry-Aware Scene Text Detection with Instance Transformation Network", IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018. [PDF]

A. Maksai, X. Wang, F. Fleuret, and P. Fua, "Globally consistent multi-people tracking using motion patterns", 
IEEE International Conference on Computer Vision (ICCV), 2017. [PDF] [Code]

X. Yu, T. Liu, X. Wang and D. Tao, "On Compressing Deep Models by Low Rank and Sparse Decomposition", IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. (spotlight oral, acceptance rate = 8.0%). [PDF


A. Maksai, X. Wang and P. Fua, "What Players do with the Ball: A Physically Constrained Interaction Modeling", IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016. (spotlight oral, acceptance rate = 9.6%) [PDF] [Project] [Code]

X. Wang, E. Türetken, F. Fleuret and P. Fua, "Tracking Interacting Objects Optimally Using Integer Programming", European Conference on Computer Vision (ECCV), 2014. (oral, acceptance rate = 2.6%) [PDF] [Talk] [Project] [Code]


Z. Wang, J. Liu, S. Huang, X. Wangand S. Chang, "Transformed Anti-Sparse Learning for Unsupervised Hashing", British Machine Vision Conference (BMVC), 2017. [PDF] [Code]

V. BelagiannisX. WangB. Schiele, P. Fua, S. Ilic and N. Navab, "Multiple Human Pose Estimation with Temporally Consistent 3D Pictorial Structures", European Conference on Computer Vision (ECCV), ChaLearn Looking at People Workshop, 2014. [PDF] [Project]


X. Wang, V. H. Ablavsky, H. Ben Shitrit and P. Fua, "Take your Eyes of the Ball: Improving Ball-Tracking by Focusing on Team Play", Computer Vision and Image Understanding (CVIU), 2014. [PDF][Project][Game]

V. Belagiannis, X. WangH. Ben Shitrit, K. Hashimoto, R. Stauder, Y. Aoki, M. Kranzfelder, A. Schneider, P. Fua, S. Ilic, H. Feussner and N. Navab, "Parsing Human Skeletons in an Operating Room", Machine Vision and Applications (MVA), 2016. [PDF] [Project]

B. Tekin, X. Sun, X. Wang, V. Lepetit and P. Fua, "Predicting People's 3D Poses from Short Sequences", CoRR abs/1504.08200. [PDF] [Project]

X. Wang, W. Bian and D. Tao, "Grassmannian Regularized Structured Multi-View Embedding for Image Classification", IEEE Transactions on Image Processing (TIP), 2013. [PDF]

X. Wang, Z. Li and D. Tao, "Subspaces Indexing Model on Grassmann Manifold for Image Search", IEEE Transactions on Image Processing (TIP), 2011. [PDF]

X. Wang, Z. Li, L. Zhang and J. Yuan, "Grassmann Hashing for approximate nearest neighbor search in high dimensional space", IEEE International Conference on Multimedia and Expo (ICME), 2011. [PDF]


Thesis

X. Wang, "Tracking Interacting Objects in Image Sequences", Ph.D. Thesis, EPFL. [PDF]