Professor Xu, Dong

PhD USTC
Professor


Fax: (+852) 2559 8447
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Dong Xu received the B.Eng. and PhD degrees from University of Science and Technology of China (USTC), in 2001 and 2005, respectively. While pursuing the PhD degree, he worked at Microsoft Research Asia as an intern and The Chinese University of Hong Kong as a research assistant for more than two years. He also worked as a postdoctoral research scientist at Columbia University, a tenure-track and tenured faculty member at Nanyang Technological University, and Chair in Computer Engineering at The University of Sydney.

His current research interests include computer vision, multimedia, and machine learning. His group has developed new machine learning methods and intelligent systems for a broad range of vision and multimedia related applications such as autonomous driving, AR/VR, video compression and surveillance, as well as medical image analysis. He has published more than 150 papers in IEEE Transactions and leading conferences including CVPR, ICCV, ECCV, ICML, ACM MM and MICCAI. His co-authored works (with his former PhD students) received the Best Student Paper Award in CVPR 2010 and the IEEE Transactions on Multimedia Prize Paper Award in 2014.

He is/was on the editorial boards of ACM Computing Surveys, IEEE Transactions including T-PAMI, T-IP, T-NNLS, T-CSVT and T-MM, and other five journals, and served as a guest editor of more than ten special issues in multiple journals (e.g., IJCV, IEEE/ACM Transactions). He will serve/served as the Program Coordinator of ACM Multimedia 2024, a steering committee member of ICME (2016-2017) and a Program Co-chair of five international conferences/workshops (e.g., ACM Multimedia Asia 2021, MLSP 2021 and ICME 2014). He was also involved in the organization committees of many international conferences and served as an area chair of leading conferences such as ICCV, CVPR, ECCV, ACM MM and AAAI. He received the Best Associate Editor Award of T-CSVT in 2017. He is a Foreign Member of the Academia Europaea and a Fellow of the IEEE and IAPR.

Research Interests

Artificial Intelligence, Computer Vision, Multimedia and Machine Learning

Selected Publications

  • R. Su, D. Xu, L. Zhou and W. Ouyang, “Progressive Cross-stream Cooperation in Spatial and Temporal Domain for Action Localization,” IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 43(12), pp. 4477-4490, December 2021.
  • W. Zhang, D. Xu, W. Ouyang and W. Li, “Self-Paced Collaborative and Adversarial Network for Unsupervised Domain Adaptation,” IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 43(6), pp. 2047-2061, June 2021.
  • W. Li, Z. Xu, D. Xu, D. Dai and L. Van Gool, “Domain Generalization and Adaptation using Low Rank Exemplar SVMs,” IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 40(5), pp. 1114-1127, May 2018.
  • X. Xu, W. Li, D. Xu and I. W. Tsang, “Co-Labeling for Multi-view Weakly Labeled Learning,” IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 38(6), pp. 1113-1125, June 2016.
  • W. Li, L. Duan, D. Xu and I. W. Tsang, “Learning with Augmented Features for Supervised and Semi-supervised Heterogeneous Domain Adaptation,” IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 36(6), pp. 1134-1148, June 2014.
  • L. Duan, D. Xu, I. W. Tsang and J. Luo, “Visual Event Recognition in Videos by Learning from Web Data,” IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 34(9), pp. 1667-1680, September 2012 (the conference version of this work won the Best Student Paper Award in CVPR 2010).
  • Y. Yang, F. Nie, D. Xu, J. Luo, Y. Zhuang and Y. Pan, “A Multimedia Retrieval Framework based on Semi-Supervised Ranking and Relevance Feedback,” IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 34(4), pp. 723-742, April 2012.
  • L. Duan, I. W. Tsang and D. Xu, “Domain Transfer Multiple Kernel Learning,” IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 34(3), pp. 465-479, March 2012.
  • D. Xu, S. Yan, S. Lin, T. S. Huang and S.-F. Chang, “Enhancing Bilinear Subspace Learning by Element Rearrangement,” IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 31(10), pp. 1913-1920, October 2009.
  • D. Xu and S.-F. Chang, “Video Event Recognition using Kernel Methods with Multilevel Temporal Alignment,” IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 30(11), pp. 1985-1997, November 2008.