Prof. Guo-Jun Qi was a technical VP and the Chief Scientist in Futurewei Technologies (Huawei Research America) based in Bellevue, WA, overseeing and leading the R&D for multiple cloud computing services, including Smart Cities, Visual Computing, Satellite Remoting Sensing, Vechicle Networking, and Autonomous Driving, and then founded the OPPO Research Center based in Seattle and several other cities across countries.  He is a Changjiang Chair Professor at Westlake University, the first private non-profit research-oriented university based in Hangzhou.  Previously,  he was a faculty member and the director of MAPLE (MAchine Perception and LEarning) lab at Computer Science Department in the University of Central Florida, and a Research Staff Member at the IBM T.J. Watson Research Center (Yorktown Heights, NY).  Before that, he worked in National University of Singapore and Microsoft Research Asia.  He received Bachelor and Ph.D. degrees from the University of Science and Technology of China and the University of Illinois at Urbana-Champaign.

He is a Fellow of IEEE, IAPR and AAIA, as well as an ACM Distinguished Scientist and a Life Member of AAAI.

Prof. Qi’s main research interests include pattern recognition, multimedia analysis, and computer vision. Particularly, he is interested in developing computational methods and theory for general-purpose AI systems to process, analyze and generate diverse modalities of data (e.g., images, audios, sensors and text) in an open connected environment (e.g., camera, sensor, mobile and social networks), enabling effective situation awareness and reliable decision-making, as well as generating 2D/3D contents across modalities. His research results have been published in many venues, including ACM Multimedia, CVPR, ICCV, ICIP, ICML, NeurIPS, KDD, IEEE T-CSVT, IEEE T-MM,  IEEE T-PAMI, IEEE T-IP, IEEE T-KDE, and Proceedings of IEEE.

Prof. Qi was the Lead General Chair of IEEE ICME 2021, and a Program Committee Chair for ACM MM 2020, ACM ICIMCS 2018 and  MMM 2016. He is/was an associate editor for IEEE Transactions on Image Processing (T-IP), IEEE Transactions on Multimedia (T-MM), IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT), ACM Transactions on Knowledge Discovery from Data (T-KDD), and Elsevier Journals on Pattern Recognition.  He is/was am an elected member of IEEE Image, Video, and Multidimensional Signal Processing (IVMSP), Multimedia  Signal Processing (MMSP), and Visual Signal Processing and Communications (VSPC) Technical Committees. He has served or will serve as Area Chair (Senior Program Committee Member) for ISCAS, ICIP, ICCV, ICME, ACM Multimedia, KDD, and CIKM, as well as Program Committee Member for ISCAS, ICASSP, CVPR, ICCV, NIPS and ICIP.   In addition, he has co-edited special issues of "Representation Learning for Visual Content Understanding," "Deep Learning for Multimedia Computing" and "Big Media Data: Understanding, Search and Mining" for IEEE. T. Circuits and Systems for Video Technology, IEEE T. Multimedia and IEEE T. Big Data respecitvely. He also served as a panelist for NSF, DoE, Sigapore AI program, Dutch Research Council (NWO), Hong Kong Research Grant Council. He is a member of IEEE Fellow Committee, and IEEE Signal Processing Society Conference Board.

1. Tingting Liao, Xiaomei Zhang, Yuliang Xiu, Hongwei Yi, Xudong Liu, Guo-Jun Qi, Yong Zhang, Xuan Wang, Xiangyu Zhu, Zhen Lei. High-fidelity Clothed Avatar Reconstruction from a Single Image,  in Proceedings of IEEE/CVF Conferences on Computer Vision and Pattern Recognition (CVPR 2023), Vancouver, Canada, June 18-22, 2023.

2. Zhiyuan Ma , Xiangyu Zhu, Guo-Jun Qi, Zhen Lei, Lei Zhang. OTAvatar: One-shot Talking Face Avatar with Controllable Tri-plane Rendering, in Proceedings of IEEE/CVF Conferences on Computer Vision and Pattern Recognition (CVPR 2023), Vancouver, Canada, June 18-22, 2023.

3. Ce Zheng, Xianpeng Liu, Guo-Jun Qi, Chen Chen. POTTER: Pooling Attention Transformer for Efficient Human Mesh Recovery,  in Proceedings of IEEE/CVF Conferences on Computer Vision and Pattern Recognition (CVPR 2023), Vancouver, Canada, June 18-22, 2023.

4. Ce Zheng, Matias Mendieta, Taojiannan Yang, Guo-Jun Qi, Chen Chen. FeatER: An Efficient Network for Human Reconstruction via Feature Map-Based TransformER, in Proceedings of IEEE/CVF Conferences on Computer Vision and Pattern Recognition (CVPR 2023), Vancouver, Canada, June 18-22, 2023.

5. Si Chen, Mostafa Kahla, Ruoxi Jia, Guo-Jun Qi*. Knowledge-Enriched Distributional Model Inversion Attacks, in Proceedings of IEEE/CVF Conferences on Computer Vision (ICCV 2021), Virtual, October 11 - October 17, 2021.

6. Qianjiang Hu, Xiao Wang, Wei Hu, Guo-Jun Qi*. AdCo: Adversarial Contrast for Efficient Learning of Unsupervised Representations from Self-Trained Negative Adversaries, in Proceedings of IEEE/CVF Conferences on Computer Vision and Pattern Recognition (CVPR 2021), Virtual, June 19th - June 25th, 2021.

7. Xu Yang, Hanwang Zhang, Guo-Jun Qi, Jianfei Cai. Causal Attention for Vision-Language Tasks, in Proceedings of IEEE/CVF Conferences on Computer Vision and Pattern Recognition (CVPR 2021), Virtual, June 19th - June 25th, 2021.

8. Muhammad Abdullah Jamal§, Guo-Jun Qi*. Task Agnostic Meta-Learning for Few-Shot Learning, in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2019), Long Beach, CA, June 16th - June 20th, 2019.

9. Guo-Jun Qi. Loss-Sensitive Generative Adversarial Networks on Lipschitz Densities, to appear in International Journal of Computer Vision (IJCV), 2019.

10. Guo-Jun Qi, Xian-Sheng Hua, Yong Rui, Jinhui Tang, Tao Mei, Hong-Jiang Zhang.Correlative Multi-Label Video Annotation, in ACM Multimedia 2007 (ACM MM 2007), Augsburg, Germany, Sep. 23-29, 2007. (Full Paper, Oral Presentation). Best Paper Award

Email: maple_hr@westlake.edu.cn

We have several open positions for postdocs, graduate students and research assistants. Our lab is committed to training the next generation of scientists. We endeavor to provide an innovative, rigorous, and collegial research environment for our trainees, and offer continuous support for the career growth of young scientists.

Please visit http://maple-lab.net/index.html for more information