Dong Gong

I am a Research Fellow at Australian Institute for Machine Learning (AIML), a Principal Researcher at Centre for Augmented Reasoning (CAR), The University of Adelaide, working with Prof. Anton van den Hengel, Prof. Qinfeng (Javen) Shi and Prof. Chunhua Shen. I obtained my PhD and B.S. in computer science from Northwestern Polytechnical University in 2018 and 2012, advised by Prof. Yanning Zhang. I spent two years at The University of Adelaide during my PhD studies, working with Javen and Anton. I will start as a Lecturer (a.k.a. Assistant Professor) at UNSW in early 2022. I will be recruiting PhD/MS students; details are coming soon. Feel free to drop me an email with your CV. [Github] [Google Scholar] [Twitter]

News

• (Sep  2021) 1 paper (about HDR imaging) accepted to appear in IJCV.

• (July 2021) 1 paper (Memory-augmented Neural Relational Inference) accepted to appear at ICCV 2021

• (July 2021) I will be a co-lecturer on Introduction to Statistical Machine Learning at UoA this semester, and give guest lectures at Deep Learning Fundamentals.

• (Dec 2020) 1 paper (unpaired domain-adaptive learning for realistic SR) accepted to appear in TIP

• (Oct  2020) 1 paper (learning attention model for vehicle retrieval) accepted to appear in TITS

• (Sep  2020) I am giving lectures at UoA Deep Learning Fundamentals on RNN, Attention, & Memory Networks.

• (July 2020) 1 paper (memory network for 3D point cloud with long-tail dist.) accepted to appear at ECCV 2020

• (Jan  2020) 1 paper (on learning to optimize for image deconv.) accepted to appear in TNNLS

• (July 2019) 1 paper (MemAE) accepted to appear at ICCV 2019

• (July 2019) 1 paper (about Sparse PCA) accepted to appear in TKDE

• (Jun  2019) 2nd Prize of OZ Minerals Explorer Challenge as part of DeepSightX team

• (Mar 2019) 1 paper accepted to appear in TKDE

• (Feb  2019) 4 papers accepted to appear at CVPR 2019

• (Nov 2018) 1 paper (on Blind Image Quality Assessment) accepted to appear in TIP

• (Oct  2018) 1 paper (about MRF based Compressive Sensing) accepted to appear in TIP

• (Sep  2018) 1 paper (MPTV) accepted to appear in TIP

• (July 2018) 2 papers accepted to appear at ECCV 2018

• (Oct  2017) Participated in ICCV 2017 Doctoral Consortium with a travel award

• (July 2017) 1 paper accepted to appear at ICCV 2017

• 1 paper accepted to appear at CVPR 2017

• 1 new arXiv paper on deep learning for motion estimation and blur removal

• 1 paper accepted to appear at AAAI 2017 as an oral

Research Interests

I have broad interests in machine learning and computer vision. My current major research topics are about:

• low/high-level computer vision

• deep/sparse modeling, optimization and learning, e.g.,
  - memory mechanism in deep learning
  - optimization + learning/sparsity

• learning with low supervision, e.g.,
  - unsupervised/semi-supervised/cross-domain learning

• interdisciplinary problems

Contact

Office: Level 2, AIML Building, Lot Fourteen, Corner of North Terrace & Frome Road, Adelaide

Email : edgong01 at gmail.com, dong.gong at adelaide.edu.au