Dr Dong Gong
Senior Lecturer

Dr Dong Gong

Engineering
Computer Science and Engineering

Homepage - https://donggong1.github.io/

Dong Gong is a Senior Lecturer and ARC DECRA Fellow (2023 - 2026) in the School of Computer Science and Engineering (CSE), UNSW Sydney. He is also an Adjunct Lecturer with the Australian Institute for Machine Learning (AIML) of The University of Adelaide. Before joining UNSW, he was a Research Fellow at the Australian Institute for Machine Learning (AIML) and a Principal Researcher at the Centre for Augmented Reasoning (CAR) of the University of Adelaide. 

His research area is Computer Vision (CV), Machine Learning (ML), Deep Learning (DL), and general Artificial Intelligence (AI) topics. He has been actively publishing in the top venues, including CVPR, ICCV, ECCV, NeurIPS, ICLR, AAAI, IJCV, TIP, etc. He is focusing on developing generalizable, reliable, and efficient computer vision (CV) and machine learning (ML) approaches for applications in real-world scenarios. 

His current research topics include:

  • machine learning methods and tasks with non-ideal supervision, e.g.,
    • continual learning
    • out-of-distribution(OOD)/anomaly/novelty/outlier detection
    • semi-supervised/domain-adaptive/unsupervised learning
  • 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 neural network (DNN) designing and training, e.g.,
    • memory mechanism in deep learning
    • training and adaptation of pre-trained large foundation models
  • interdisciplinary problems

 

I am continually seeking highly motivated PhD, MPhil, and visiting students with passion and a strong background in computer vision and machine learning. 

 

Current undergraduate students or master by course students at UNSW are encouraged to contact me if you are interested in research degrees (Master by research or PhD) or research projects (honors thesis project or master research project) in CV, ML, and related topics. 

Please check the details and email me your CV and transcripts if you are interested. 

Location
Level 4, Building K17
  • Journal articles | 2023
    Yan Q; Fruzangohar M; Taylor J; Gong D; Walter J; Norman A; Shi JQ; Coram T, 2023, 'Improved genomic prediction using machine learning with Variational Bayesian sparsity', Plant Methods, 19, http://dx.doi.org/10.1186/s13007-023-01073-3
    Journal articles | 2023
    Yan Q; Gong D; Wang P; Zhang Z; Zhang Y; Shi JQ, 2023, 'SharpFormer: Learning Local Feature Preserving Global Representations for Image Deblurring', IEEE Transactions on Image Processing, 32, pp. 2857 - 2866, http://dx.doi.org/10.1109/TIP.2023.3251029
    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, 126, http://dx.doi.org/10.1016/j.patcog.2022.108577
    Journal articles | 2022
    Yan Q; Gong D; Shi JQ; den Hengel AV; Sun J; Zhu Y; Zhang Y, 2022, 'High dynamic range imaging via gradient-aware context aggregation network', Pattern Recognition, 122, http://dx.doi.org/10.1016/j.patcog.2021.108342
    Journal articles | 2022
    Yan Q; Gong D; Shi JQ; van den Hengel A; Shen C; Reid I; Zhang Y, 2022, 'Dual-Attention-Guided Network for Ghost-Free High Dynamic Range Imaging', International Journal of Computer Vision, 130, pp. 76 - 94, http://dx.doi.org/10.1007/s11263-021-01535-y
    Journal articles | 2022
    Zhang X; Zhang R; Cao J; Gong D; You M; Shen C, 2022, 'Part-Guided Attention Learning for Vehicle Instance Retrieval', IEEE Transactions on Intelligent Transportation Systems, 23, pp. 3048 - 3060, http://dx.doi.org/10.1109/TITS.2020.3030301
    Journal articles | 2021
    Lu W; Gong D; Fu K; Sun X; Diao W; Liu L, 2021, 'Boundarymix: Generating pseudo-training images for improving segmentation with scribble annotations', Pattern Recognition, 117, http://dx.doi.org/10.1016/j.patcog.2021.107924
    Journal articles | 2021
    Sun W; Gong D; Shi Q; Van Den Hengel A; Zhang Y, 2021, 'Learning to Zoom-In via Learning to Zoom-Out: Real-World Super-Resolution by Generating and Adapting Degradation', IEEE Transactions on Image Processing, 30, pp. 2947 - 2962, http://dx.doi.org/10.1109/TIP.2021.3049951
    Journal articles | 2021
    Tan M; Hu Z; Yan Y; Cao J; Gong D; Wu Q, 2021, 'Learning Sparse PCA with Stabilized ADMM Method on Stiefel Manifold', IEEE Transactions on Knowledge and Data Engineering, 33, pp. 1078 - 1088, http://dx.doi.org/10.1109/TKDE.2019.2935449
    Journal articles | 2021
    Wang Y; Gong D; Yang J; Shi Q; Hengel AVD; Xie D; Zeng B, 2021, 'Deep Single Image Deraining via Modeling Haze-Like Effect', IEEE Transactions on Multimedia, 23, pp. 2481 - 2492, http://dx.doi.org/10.1109/TMM.2020.3013383
    Journal articles | 2021
    Wang Y; Qi Y; Yao H; Gong D; Wu Q, 2021, 'Image editing with varying intensities of processing', Computer Vision and Image Understanding, 211, http://dx.doi.org/10.1016/j.cviu.2021.103260
    Journal articles | 2021
    Yan Q; Wang B; Gong D; Luo C; Zhao W; Shen J; Ai J; Shi Q; Zhang Y; Jin S; Zhang L; You Z, 2021, 'COVID-19 Chest CT image segmentation network by multi-scale fusion and enhancement operations', IEEE Transactions on Big Data, 7, pp. 13 - 24, http://dx.doi.org/10.1109/TBDATA.2021.3056564
    Journal articles | 2020
    Gong D; Zhang Z; Shi Q; Van Den Hengel A; Shen C; Zhang Y, 2020, 'Learning Deep Gradient Descent Optimization for Image Deconvolution', IEEE Transactions on Neural Networks and Learning Systems, 31, pp. 5468 - 5482, http://dx.doi.org/10.1109/TNNLS.2020.2968289
    Journal articles | 2020
    Liu W; Gong D; Tan M; Shi JQ; Yang Y; Hauptmann AG, 2020, 'Learning Distilled Graph for Large-Scale Social Network Data Clustering', IEEE Transactions on Knowledge and Data Engineering, 32, pp. 1393 - 1404, http://dx.doi.org/10.1109/TKDE.2019.2904068
    Journal articles | 2019
    Gong D; Tan M; Shi Q; Van Den Hengel A; Zhang Y, 2019, 'MPTV: Matching pursuit-based total variation minimization for image deconvolution', IEEE Transactions on Image Processing, 28, pp. 1851 - 1865, http://dx.doi.org/10.1109/TIP.2018.2875352
    Journal articles | 2019
    Li R; Sun J; Gong D; Zhu Y; Li H; Zhang Y, 2019, 'ARSAC: Efficient model estimation via adaptively ranked sample consensus', Neurocomputing, 328, pp. 88 - 96, http://dx.doi.org/10.1016/j.neucom.2018.02.103
    Journal articles | 2019
    Suwanwimolkul S; Zhang L; Gong D; Zhang Z; Chen C; Ranasinghe DC; Qinfeng Shi J, 2019, 'An adaptive markov random field for structured compressive sensing', IEEE Transactions on Image Processing, 28, pp. 1556 - 1570, http://dx.doi.org/10.1109/TIP.2018.2878294
    Journal articles | 2019
    Yan Q; Gong D; Zhang Y, 2019, 'Two-Stream Convolutional Networks for Blind Image Quality Assessment', IEEE Transactions on Image Processing, 28, pp. 2200 - 2211, http://dx.doi.org/10.1109/TIP.2018.2883741
    Journal articles | 2018
    Gong D; Li R; Zhu Y; Li H; Sun J; Zhang Y, 2018, 'Blind image deblurring by promoting group sparsity', Neurocomputing, 310, pp. 190 - 200, http://dx.doi.org/10.1016/j.neucom.2018.05.025
  • Conference Papers | 2023
    Li R; Gong D; Yin W; Chen H; Zhu Y; Wang K; Chen X; Sun J; Zhang Y, 2023, 'Learning to Fuse Monocular and Multi-view Cues for Multi-frame Depth Estimation in Dynamic Scenes', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 21539 - 21548, http://dx.doi.org/10.1109/CVPR52729.2023.02063
    Conference Papers | 2022
    Perez-Pellitero E; Catley-Chandar S; Shaw R; Leonardis A; Timofte R; Zhang Z; Liu C; Peng Y; Lin Y; Yu G; Zhang J; Ma Z; Wang H; Chen X; Wang X; Wu H; Liu L; Dong C; Zhou J; Yan Q; Zhang S; Chen W; Liu Y; Zhang Z; Zhang Y; Shi JQ; Gong D; Zhu D; Sun M; Chen G; Hu Y; Li H; Zou B; Liu Z; Lin W; Jiang T; Jiang C; Li X; Han M; Fan H; Sun J; Liu S; Marin-Vega J; Sloth M; Schneider-Kamp P; Rottger R; Li C; Bao L; He G; Xu Z; Xu L; Zhan G; Sun M; Wen X; Li J; Li J; Li C; Gang R; Li F; Liu C; Feng S; Lei F; Liu R; Ruan J; Dai T; Li W; Lu Z; Liu H; Huang P; Ren G; Luo Y; Liu C; Tu Q; Li F; Gang R; Li C; Li J; Ma S; Liu C; Cao Y; Tel S; Heyrman B; Ginhac D; Lee C; Kim G; Park S; Vien AG; Thanh Nhat Mai T; Yoon H; Vo T; Holston A; Zaheer S; Park CY, 2022, 'NTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results', in IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, pp. 1008 - 1022, http://dx.doi.org/10.1109/CVPRW56347.2022.00114
    Conference Papers | 2022
    Yan Q; Gong D; Liu Y; Van Den Hengel A; Shi JQ, 2022, 'Learning Bayesian Sparse Networks with Full Experience Replay for Continual Learning', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 109 - 118, http://dx.doi.org/10.1109/CVPR52688.2022.00021
    Conference Papers | 2022
    Yan Q; Zhang S; Chen W; Liu Y; Zhang Z; Zhang Y; Shi JQ; Gong D, 2022, 'A Lightweight Network for High Dynamic Range Imaging', in IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, pp. 823 - 831, http://dx.doi.org/10.1109/CVPRW56347.2022.00098
    Conference Papers | 2022
    Zhang Z; Ng I; Gong D; Liu Y; Abbasnejad EM; Gong M; Zhang K; Shi JQ, 2022, 'Truncated Matrix Power Iteration for Differentiable DAG Learning', in Advances in Neural Information Processing Systems
    Conference Papers | 2021
    Gong D; Zhang Z; Shi JQ; van den Hengel A, 2021, 'Memory-augmented Dynamic Neural Relational Inference', in Proceedings of the IEEE International Conference on Computer Vision, pp. 11823 - 11832, http://dx.doi.org/10.1109/ICCV48922.2021.01163
    Conference Papers | 2021
    Xu HM; Liu L; Gong D, 2021, 'Semi-supervised Learning via Conditional Rotation Angle Estimation', in DICTA 2021 - 2021 International Conference on Digital Image Computing: Techniques and Applications, http://dx.doi.org/10.1109/DICTA52665.2021.9647327
    Conference Papers | 2021
    Yan Q; Wang B; Gong D; Zhang D; Yang Y; You Z; Zhang Y; Shi JQ, 2021, 'A Comprehensive CT Dataset for Liver Computer Assisted Diagnosis', in 32nd British Machine Vision Conference, BMVC 2021
    Conference Papers | 2020
    He T; Gong D; Tian Z; Shen C, 2020, 'Learning and Memorizing Representative Prototypes for 3D Point Cloud Semantic and Instance Segmentation', in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 564 - 580, http://dx.doi.org/10.1007/978-3-030-58523-5_33
    Conference Papers | 2019
    Gong D; Liu L; Le V; Saha B; Mansour MR; Venkatesh S; Van Den Hengel A, 2019, 'Memorizing normality to detect anomaly: Memory-augmented deep autoencoder for unsupervised anomaly detection', in Proceedings of the IEEE International Conference on Computer Vision, pp. 1705 - 1714, http://dx.doi.org/10.1109/ICCV.2019.00179
    Conference Papers | 2019
    He T; Shen C; Tian Z; Gong D; Sun C; Yan Y, 2019, 'Knowledge adaptation for efficient semantic segmentation', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 578 - 587, http://dx.doi.org/10.1109/CVPR.2019.00067
    Conference Papers | 2019
    Li J; Liu Y; Gong D; Shi Q; Yuan X; Zhao C; Reid I, 2019, 'RGBD based dimensional decomposition residual network for 3D semantic scene completion', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 7685 - 7694, http://dx.doi.org/10.1109/CVPR.2019.00788
    Conference Papers | 2019
    Li R; Gong D; Sun J; Zhu Y; Wei Z; Zhang Y, 2019, 'Robust and Accurate Hybrid Structure-From-Moti', in Proceedings - International Conference on Image Processing, ICIP, pp. 494 - 498, http://dx.doi.org/10.1109/ICIP.2019.8803814
    Conference Papers | 2019
    Liu Y; Dong W; Zhang L; Gong D; Shi Q, 2019, 'Variational bayesian dropout with a hierarchical prior', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 7117 - 7126, http://dx.doi.org/10.1109/CVPR.2019.00729
    Conference Papers | 2019
    Snaauw G; Gong D; Maicas G; Hengel AVD; Niessen WJ; Verjans J; Carneiro G, 2019, 'End-to-end diagnosis and segmentation learning from cardiac magnetic resonance imaging', in Proceedings - International Symposium on Biomedical Imaging, pp. 802 - 805, http://dx.doi.org/10.1109/ISBI.2019.8759276
    Conference Papers | 2019
    Yan Q; Gong D; Shi Q; Van Den Hengel A; Shen C; Reid I; Zhang Y, 2019, 'Attention-guided network for ghost-free high dynamic range imaging', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 1751 - 1760, http://dx.doi.org/10.1109/CVPR.2019.00185
    Conference Papers | 2019
    Yan Q; Gong D; Zhang P; Shi Q; Sun J; Reid I; Zhang Y, 2019, 'Multi-scale dense networks for deep high dynamic range imaging', in Proceedings - 2019 IEEE Winter Conference on Applications of Computer Vision, WACV 2019, pp. 41 - 50, http://dx.doi.org/10.1109/WACV.2019.00012
    Conference Papers | 2018
    Liu Y; Dong W; Gong D; Zhang L; Shi Q, 2018, 'Deblurring Natural Image Using Super-Gaussian Fields', in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 467 - 484, http://dx.doi.org/10.1007/978-3-030-01246-5_28
    Conference Papers | 2018
    Yang J; Gong D; Liu L; Shi Q, 2018, 'Seeing Deeply and Bidirectionally: A Deep Learning Approach for Single Image Reflection Removal', in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 675 - 691, http://dx.doi.org/10.1007/978-3-030-01219-9_40
    Conference Papers | 2017
    Gong D; Tan M; Zhang Y; Hengel AVD; Shi Q, 2017, 'Self-Paced Kernel Estimation for Robust Blind Image Deblurring', in Proceedings of the IEEE International Conference on Computer Vision, pp. 1670 - 1679, http://dx.doi.org/10.1109/ICCV.2017.184
    Conference Papers | 2017
    Gong D; Tan M; Zhang Y; Van Den Hengel A; Shi Q, 2017, 'MPGL: An efficient matching pursuit method for generalized LASSO', in 31st AAAI Conference on Artificial Intelligence, AAAI 2017, pp. 1934 - 1940
    Conference Papers | 2017
    Gong D; Yang J; Liu L; Zhang Y; Reid I; Shen C; Van Den Hengel A; Shi Q, 2017, 'From motion blur to motion flow: A deep learning solution for removing heterogeneous motion blur', in Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, pp. 3806 - 3815, http://dx.doi.org/10.1109/CVPR.2017.405
    Conference Papers | 2016
    Gong D; Tan M; Zhang Y; Hengel AVD; Shi Q, 2016, 'Blind Image Deconvolution by Automatic Gradient Activation', in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 1827 - 1836, http://dx.doi.org/10.1109/CVPR.2016.202
    Conference Papers | 2014
    Ding W; Gong D; Zhang Y; He Y, 2014, 'Centroid estimation based on MSER detection and Gaussian Mixture Model', in International Conference on Signal Processing Proceedings, ICSP, pp. 774 - 779, http://dx.doi.org/10.1109/ICOSP.2014.7015109
    Conference Papers | 2014
    Li H; Zhang Y; Sun J; Gong D, 2014, 'Joint motion deblurring with blurred/noisy image pair', in Proceedings - International Conference on Pattern Recognition, pp. 1020 - 1024, http://dx.doi.org/10.1109/ICPR.2014.185
    Conference Papers | 2013
    Dang S; Zhang Y; Gong D, 2013, 'A patch-based non-local means method for image denoising', in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 582 - 589, http://dx.doi.org/10.1007/978-3-642-36669-7_71
    Conference Papers | 2013
    Gong D; Zhang Y; Dang S; Sun J, 2013, 'Neighbor combination for atmospheric turbulence image reconstruction', in 2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings, pp. 1361 - 1365, http://dx.doi.org/10.1109/ICIP.2013.6738280