Computer Vision Group,
    School of Electronic Engineering and Computer Science,
    Queen Mary University of London,
    London E1 4NS,
    United Kingdom.

    Email: q.dong AT qmul.ac.uk

QI DONG is a PhD student (the second year) in the Computer Vision Group of Queen Mary University of London (QMUL), under the supervision of Prof. Shaogang Gong. Prior to joining QMUL, she received the M.Eng. degree in Computer Science from National Key Laboratory of Fundamental Science on Synthetic Vision, Sichuan University, Sichuan, PRC., and the B.Eng in Computer Science from Tianjin University of Technology, Tianjin, PRC.. Her research interests include Computer Vision and Machine Learning, particularly in Deep learning and Attribute analysis.


Qi Dong, Shaogang Gong, Xiatian Zhu. Imbalanced Deep Learning by Minority Class Incremental Rectification. IEEE Transactions on Pattern Analysis and Machine Intelligence, accepted, 2018. (TPAMI).   [PDF][Project page]


Qi Dong, Shaogang Gong, Xiatian Zhu. Class Rectification Hard Mining for Imbalanced Deep Learning. In Proc. International Conference on Computer Vision, Venice, Italy, Oct 2017 (ICCV2017).   [PDF]


Qi Dong, Shaogang Gong, Xiatian Zhu. Multi-Task Curriculum Transfer Deep Learning of Clothing Attributes. In Proc. IEEE Winter Conference on Applications of Computer Vision, Santa Rosa, CA, USA, March 2017 (WACV2017).   [PDF]


Qi Dong, Yanli Liu, Qijun Zhao, Hongyu Yang. Detecting soft shadows in a single outdoor image: From local edge-based models to global constraints. In Computers & Graphics, Volume 38, February 2014, Pages 310-319. (CG)   [PDF]  


Updated Dec 2016
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