Workshop on Learning and Inference Methods for High Performance Imaging

Wanli Ouyang

The University of Sydney, Australia

Wanli Ouyang received the PhD degree in the Department of Electronic Engineering, The Chinese University of Hong Kong. He is now a senior lecturer at the University of Sydney. His research interests include deep learning for image processing, computer vision and pattern recognition. He is the first author of 7 papers on TPAMI and IJCV. ImageNet Large Scale Visual Recognition Challenge (ILSVRC) is one of the most important grand challenges in computer vision. The team led or supervised by him ranks No. 1 in the ILSVRC 2015, ILSVRC 2016, and COCO 2018. He receives the best reviewer award of ICCV and is the guest editor of IJCV. He has been the reviewer of many top journals and conferences such as IEEE TPAMI, TIP, IJCV, SIGGRAPH, CVPR, and ICCV. He is a senior member of the IEEE.

Boxin Shi

Peking University, China

Boxin earned his Ph.D. degree in information science and technology from the University of Tokyo and currently leads the Camera Intelligence group at the Institute of Digital Media, School of Electronics Engineering and Computer Science, Peking University (1000 Youth Talents Professorship, 青年千人研究员、博士生导师). Before joining Peking University, he worked as a Researcher at the Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology (AIST). He has also worked as a Research Fellow at the Rapid-Rich Object Search (ROSE) Lab at Nanyang Technological University, at the Camera Culture Group at the MIT Media Lab and the Vision, Graphics, and Computational Design (VDG) group at Singapore University of Technology and Design. He won the Best Paper Runner-up award at International Conference on Computational Photography 2015 and was invited to publish on IJCV special issue of Best Papers of ICCV 2015. He served/is serving as an Area Chair for ACCV 2018, MVA 2019, 2017.