When: Weds 27th of November, 4pm
Where: Rose St Building seminar area
Speaker: Wanli Ouyang, School of Electrical & Information Engineering
Title: Exploring Deep Structures in Computer Vision Tasks
Abstract: Structure in data provide rich information that helps to reduce the complexity and improves the effectiveness of a model. In this talk, an introduction will be given on the recent progress in using deep learning as a tool for modeling the structure in visual data. We show that observation in our problem are useful in modeling the structure of deep model and help to improve the effectiveness of deep models for many vision problems.
Bio: 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 image processing, computer vision and pattern recognition. He is the first author of 7 papers on TPAMI and IJCV. He received the best reviewer award of ICCV. He serves as the guest editor for IJCV, demo chair for ICCV 2019. 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.