Tao Wang

Object detection and segmentation, context modeling for scene understanding, learning and inference for computer vision

Ph.D. NICTA Canberra Research Lab, College of Engineering & Computer Science, The Australian National University (Supervisors: Xuming He and Nick Barnes)
B.Eng. School of Electronic & Information Engineering, South China University of Technology (Supervisor: Lianwen Jin)

Lecturer, College of Computer and Control Engineering, Minjiang University (2017 - present)
Researcher, NetDragon R&D Fuzhou (2016 - present)
Research Programmer, NICTA Canberra Research Lab (2012 - 2014)

• Introduction to Artificial Intelligence (Fall 2017, Spring 2019)
• More...

• Tao Wang, Xuming He, Songzhi Su, Yin Guan. Efficient Scene Layout Aware Object Detection for Traffic Surveillance, IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2017. (Traffic Surveillance Workshop and Challenge Best Paper Award)
• Tao Wang, Xuming He, Nick Barnes. Learning Structured Hough Voting for Joint Object Detection and Occlusion Reasoning, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2013.
• Tao Wang, Xuming He, Nick Barnes. Glass Object Segmentation by Label Transfer on Joint Depth and Apearance Manifolds, IEEE International Conference on Image Processing (ICIP), 2013.
• Tao Wang, Xuming He, Nick Barnes. Learning Hough Forest with Depth-Encoded Context for Object Detection, IEEE International Conference on Digital Image Computing: Techniques and Applications (DICTA), 2012.
• Tao Wang, Xuming He, Nick Barnes. Glass Object Localization by Joint Inference of Boundary and Depth, IEEE International Conference on Pattern Recognition (ICPR), 2012.
• Tao Wang, Xuming He, Chunhua Shen, Nick Barnes. Laplacian Margin Distribution Boosting for Learning from Sparsely Labeled Data, IEEE International Conference on Digital Image Computing: Techniques and Applications (DICTA), 2011.

• Reviewer, IET Computer Vision, IET Image Processing, Machine Vision and Applications
• PC Member, IJCAI 2018, AAAI 2019