Tel.: 3917 8481
Office: CB 518
My research aims at endowing machine with the capability to perceive, understand, and reconstruct the visual world. Currently, my research focus is on: 1) developing scalable and label-efficient deep learning algorithms for natural image and medical image analysis; 2) designing effective techniques for 3D scene understanding and reconstruction; 3) understanding the behaviors of deep neural networks in out-of-distribution data.
Biography– Dr. Xiaojuan Qi is currently an Assistant Professor in Department of Electrical and Electronic Engineering, The University of Hong Kong. Before joining HKU, she was a postdoctoral researcher at the University of Oxford, UK. She received her PhD from The Chinese University of Hong Kong (CUHK) in 2018 and her BEng from Shanghai Jiao Tong University (SJTU) in 2014. From September 2016 to November 2016, she was a visiting student in the Machine Learning Group, University of Toronto. She has carried out an internship at Intel Intelligent Systems Lab from May 2017 to November 2017. She has won several awards such as the first place of ImageNet Semantic Parsing Challenge, Outstanding Reviewer in ICCV’17 and ICCV’19, CVPR’18 Doctoral Consortium Travel Award and Hong Kong PhD Fellowship (2014 – 2018).
- Xiaojuan Qi, Zhengzhe Liu, Qifeng Chen, Jiaya Jia, 3D Motion Decomposition for RGBD Future Dynamic Scene Synthesis, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
- Xiaojuan Qi, Renjie Liao, Zhengzhe Liu, Raquel Urtasun, Jiaya Jia, GeoNet: Geometric Neural Network for Joint Depth and Surface Normal Estimation. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
- Xiaojuan Qi, Qifeng Chen, Jiaya Jia, Vladlen Koltun, Semi-parametric Image Synthesis, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
- Hengshuang Zhao, Jianping Shi, Xiaojuan Qi, Xiaogang Wang, Jiaya Jia. Pyramid Scene Parsing Network, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.
- Xiaojuan Qi, R.J. Liao, Jiaya Jia, Sanja Fidler, Raquel Urtasun, 3D Graph Neural Networks for RGBD Semantic Segmentation, IEEE Conference on Computer Vision (ICCV), 2017.
- Xiaojuan Qi, Zhengzhe Liu, Jianping Shi, Hengshuang Zhao, Jiaya Jia, Augmented Feedback in Semantic Segmentation under Image Level Supervision, European Conference on Computer Vision (ECCV), 2016.