Tao Wang

Tao Wang

Lecturer

Minjiang University

Biography

I am a Lecturer in the College of Computer and Control Engineering, Minjiang University. Prior to this, I was a PhD student at The Australian National University, working with Xuming He and Nick Barnes. I was also a member of the Computer Vision Research Group, National ICT Australia, Canberra.

Interests

  • Object detection and segmentation
  • Context modeling for scene understanding
  • Learning and inference for computer vision

Education

  • Ph.D. in Computer Science, 2016

    The Australian National University

  • B.E. in Information Engineering, 2009

    South China University of Technology

Publications

A Multi-Level Approach to Waste Object Segmentation
A Multi-Level Approach to Waste Object Segmentation. Sensors, 2020.

Learning a Layout Transfer Network for Context Aware Object Detection
Learning a Layout Transfer Network for Context Aware Object Detection. IEEE Transactions on Intelligent Transportation Systems (T-ITS), 2019.

Efficient Scene Layout Aware Object Detection for Traffic Surveillance
Efficient Scene Layout Aware Object Detection for Traffic Surveillance. IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Traffic Surveillance Workshop and Challenge Best Paper Award, 2017.

Glass Object Segmentation by Label Transfer on Joint Depth and Appearance Manifolds
Glass Object Segmentation by Label Transfer on Joint Depth and Appearance Manifolds. IEEE International Conference on Image Processing (ICIP), 2013.

Learning Structured Hough Voting for Joint Object Detection and Occlusion Reasoning
Learning Structured Hough Voting for Joint Object Detection and Occlusion Reasoning. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2013.

Glass Object Localization by Joint Inference of Boundary and Depth
Glass Object Localization by Joint Inference of Boundary and Depth. IEEE International Conference on Pattern Recognition (ICPR), 2012.

Learning Hough Forest with Depth-Encoded Context for Object Detection
Learning Hough Forest with Depth-Encoded Context for Object Detection. IEEE International Conference on Digital Image Computing: Techniques and Applications (DICTA), 2012.

Laplacian Margin Distribution Boosting for Learning from Sparsely Labeled Data
Laplacian Margin Distribution Boosting for Learning from Sparsely Labeled Data. IEEE International Conference on Digital Image Computing: Techniques and Applications (DICTA), 2011.

Teaching

  • Introduction to Artificial Intelligence
  • Linux System Applications
  • Professional English for Computer Science

Services

  • Reviewer, IET Computer Vision, IET Image Processing, Machine Vision and Applications
  • PC Member, IJCAI 2018/2019/2020, AAAI 2019/2020

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