Recent Progress on Deep Learning Based Face Recognition, Analysis and Translation
Speaker:Prof. Linlin SHEN
Shenzhen University
Shenzhen
China
Date & Time:4 Jan 2019 (Friday) 11:00 - 12:00
Venue:E11-4045 (University of Macau)
Organized by:Department of Computer and Information Science

Abstract

In this talk, I will mainly introduce deep learning and its applications in face recognition, analysis and translation. The history of face recognition using hand-crafted features and deep neural networks will be firstly briefed. Publicly available face datasets for both training and testing will be introduced. The most recent progress about the performance of facial recognition algorithms and their real applications will be followed. The methodologies to address face spoofing and classification of facial attributes including age, gender and expressions will be explored. Finally, the progress about face translation using GAN, pix2pix, starGAN and our proposed GAN will be presented.

Biography

Prof. Linlin Shen is currently a professor at Computer Science and Software Engineering, Shenzhen University, Shenzhen, China. He is also an Honorary professor at School of Computer Science, University of Nottingham, UK. He serves as the director of Computer Vision Institute and China-UK joint research lab for visual information processing. He received the BSc and MEng degrees from Shanghai Jiaotong University, Shanghai, China, and the Ph.D. degree from the University of Nottingham, Nottingham, U.K. He was a Research Fellow with the University of Nottingham, working on MRI brain image processing. His research interests include deep learning, facial recognition, analysis/synthesis and medical image processing. Prof. Shen is listed as the Most Cited Chinese Researcher by Elsevier. He received the Most Cited Paper Award from the journal of Image and Vision Computing. His cell classification algorithms were the winners of the International Contest on Pattern Recognition Techniques for Indirect Immunofluorescence Images held by ICIP 2013 and ICPR 2016.