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Mr Xingshuai Dong

Mr Xingshuai Dong

Research Associate

PhD in Aerospace Engineering, University of New South Wales (UNSW), Canberra, Australia, August 2023

UNSW Canberra
School of Systems & Computing

Xingshuai Dong is currently a Research Associate at the School of Systems and Computing, UNSW Canberra. He received his PhD degree in Aerospace Engineering in August 2023. His research primarily focuses on monocular depth estimation, object detection, robotic scene understanding, and navigation. He has served as a reviewer for a number of peer-reviewed journals including IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Cybernetics, IEEE Transactions on Artificial Intelligence, IEEE Transactions on Human-Machine Systems, IEEE Robotics and Automation Letters, IEEE Access, Neural Processing Letters, and Optics Express.
E-mail
xingshuai.dong@unsw.edu.au
Location
Building 15 School of Systems and Computing UNSW Canberra Australian Defence Force Academy Canberra, ACT
  • Journal articles | 2022
    Dong X; Garratt MA; Anavatti SG; Abbass HA, 2022, 'MobileXNet: An Efficient Convolutional Neural Network for Monocular Depth Estimation', IEEE Transactions on Intelligent Transportation Systems, 23, pp. 20134 - 20147, http://dx.doi.org/10.1109/TITS.2022.3179365
    Journal articles | 2022
    Dong X; Garratt MA; Anavatti SG; Abbass HA, 2022, 'Towards Real-Time Monocular Depth Estimation for Robotics: A Survey', IEEE Transactions on Intelligent Transportation Systems, 23, pp. 16940 - 16961, http://dx.doi.org/10.1109/TITS.2022.3160741
  • Conference Papers | 2022
    Dong X; Garratt MA; Anavatti SG; Abbass HA; Dong J, 2022, 'Lightweight Monocular Depth Estimation with an Edge Guided Network', in 2022 17th International Conference on Control, Automation, Robotics and Vision, ICARCV 2022, pp. 204 - 210, http://dx.doi.org/10.1109/ICARCV57592.2022.10004313

Invited Presentations                                                                 

  • Applications of Computer Vision in Autonomous Vehicles: Methods, Challenges, and Future Directions

         The "Long Road Ahead" International Workshop on Autonomous, Connected, and Smart Transportation, UNSW Canberra, 29 June 2023