Dr Dong Gong

Dr Dong Gong

Computer Science and Engineering

Dr Dong Gong is a Lecturer in the School of Computer Science and Engineering. He is also an Adjunct Lecturer with the Australian Institute for Machine Learning (AIML) of The University of Adelaide. Befor joining UNSW, he was a Research Fellow at Australian Institute for Machine Learning (AIML), a Principal Researcher at Centre for Augmented Reasoning (CAR), The University of Adelaide. 

His research area is in Computer Vision, Machine Learning, Deep Learning, Image Restoration, and Artificial Intelligence. He has been actively publising in the top venues, including CVPR, ICCV, ECCV, AAAI, IJCV, TIP, etc. He is focusing on developing generalizable, realiable, and efficient computer vision (CV) and machine learning (ML) approaches for the applciations in real-world scenarios. 

His current research topics include:

  • low/high-level computer vision:
    • image restoration, e.g., deblurring/deconvolution, super-resolution, high dynamic range imaging, etc.
    • image/video understanding
    • 3D scene reconstruction and understanding
  • deep learning
    • memory-augmented deep learning
    • deep learning with sparsity/optimization
    • novelty/outlier/anomaly detection
    • neural relational inference
  • learning with low/non-ideal supervision
    • continual learning
    • domain-adaptive learning
    • unsupervised/semi-supervised learning
  • interdisciplinary problems

Personal website - https://donggong1.github.io/

Level 4, Building K17
  • Journal articles | 2022
    Sun W; Gong D; Shi JQ; van den Hengel A; Zhang Y, 2022, 'Video super-resolution via mixed spatial-temporal convolution and selective fusion', Pattern Recognition, vol. 126, http://dx.doi.org/10.1016/j.patcog.2022.108577