Prof. Xiaobai Li

Zhejiang University, China/University of Oulu, Finland

Dr. Xiaobai Li (Senior Member, IEEE) received the B.Sc. degree in psychology from Peking University, Beijing, the M.Sc. degree in biophysics from the Chinese Academy of Sciences, Beijing, and the Ph.D. degree in computer science and technology from the University of Oulu, Finland. She is currently a ZJU100 Professor at the Institute of Cyber Science and Technology, Zhejiang University, and she is also an Adjunct Professor at the Center for Machine Vision and Signal Analysis, University of Oulu. Her research interests include computer vision and machine learning, with a focus on facial video analysis and related applications in Biometrics, AI security and affective computing. Dr. Li chaired several international workshops at the conference on Computer Vision and Pattern Recognition (CVPR), International Conference on Computer Vision (ICCV), International Conference on Automatic Face and Gesture Recognition (FG), and ACM Multimedia. She is an Associate Editor of IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY (TCSVT), Frontiers in Psychology, and Image and Vision Computing.

Speech Title: "Remote Physiological Signal Sensing for Emotion, Health, and Security"

Abstract: Photoplethysmography (PPG) is one of the most important physiological signals of human bodies. It can not only indicate human’s health status, but also represent human’s emotional feelings and psychological status. Traditional ways of PPG measurement require contact sensors attached to human bodies, which is not convenient and constraint the applications. The report focuses on facial video-based remote PPG measurement technology. We first introduce the development of latest rPPG measurement methods, and then present its application in multiple regions including affective computing, healthcare and security.

Prof. Xiwen Zhang

Beijing Language and Culture University, China

Xiwen Zhang is currently a full professor of Digital Media Department, School of Information Science, the Beijing Language and Culture University. Prof. Zhang worked as an associated professor from 2002 to 2007 at the Human-computer interaction Laboratory, Institute of Software, Chinese Academy of Sciences. From 2005 to 2006 he was a Post doctor advised by Prof. Michael R. Lyu in the Department of Computer Science and Engineering, the Chinese University of Hong Kong. From 2000 to 2002 he was a Post doctor advised by Prof. ShiJie Cai in the Computer Science and Technology department, Nanjing University. Prof. Zhang's research interests include pattern recognition, computer vision, and human-computer interaction, as well as their applications in digital image, video, and ink. Prof. Zhang has published over 60 refereed journal and conference papers. His SCI papers are published in Pattern Recognition, IEEE Transactions on Systems, Man, and Cybernetics, Computer-Aided Design. He has published more than twenty EI paper.

Speech Title: "Three Views on Intelligently Extracting and Generating Information from Image"

Abstract: Due to pattern recognition and deep learning, various information can be extracted and generated from image. Our work has focused on using the proposed hierarchy models, local homogeneity, and adversarial generation. Various digital images are processed, such as ones scanned from mechanical paper drawings and paper text, face images, portrait ones with line drawings, and microscopic bone marrow images. Various information is extracted using the proposed hierarchy models. Graphics and their multi-levels compounded objects are extracted and recognized from images scanned from mechanical paper drawings using a hierarchy model of engineering drawings. Faces and their components are extracted from photos using a facial model. Various information is extracted using the proposed local homogeneity. Karyocytes and their components from microscopic bone marrow images based on regional color features. Various information is extracted and generated from image using cycle-Consistent adversarial networks. Text is separated from grid background using cycle-Consistent adversarial networks. Digital images of Chinese classical upper-class lady paintings are generated from images with line drawings using conditional generative adversarial networks.

Prof. Yang Yang

Anhui University, China

Yang Yang is a Professor at the School of Electronic and Information Engineering, Anhui University. She received her Ph. D. degree in Information and Communication Engineering from University of Science and Technology in 2013. She was awarded the title of "New Talent in Teaching" from Anhui Provincial Department of Education. She serves as a member of the CCF Quantum Computing Committee, a member of the CSIG Digital Forensics and Security Committee, and a member of the CSIG Female Working Committee. Her research interests include AI security, quantum artificial intelligence, and image processing technology.

Prof. Yi-Jun Yang

Xi'an Jiaotong University, China

Yi-Jun Yang is now a professor in school of computer science and technology of Xi'an Jiaotong university and R.D. director of CSSC SEAGO system and technology Co., Ltd. He received his Ph.D degree in the Department of Computer Science and Technology at Tsinghua University in 2008. He has had faculty positions in the Shandong university and has been an associate Professor in school of computer science and technology in 2012-2019. His research interests are in Computer Aided Design, Computer Graphics and most recently in Geometric Engine Architecture and Algorithms. He is a member of CCF GDC, CAD and CG Special Committee. He served as the co-organization chair of CAD/Graphics 2021 and GAMES 2021. He received the excellent achievement award of high institute in 2023.

Speech Title: "Optimal Parameterization of Freeform Surfaces"

Abstract: The parameterization of freeform surfaces plays an important role in geometric design and computer graphics. The parameterization of freeform surfaces highly affects their rendering and tessellation results. The conformality and equiareality are two key properties of the optimal parameterization. The only rational Bézier surfaces with uniform iso-parametric curves are bilinear surfaces, and the only rational Bézier surfaces with conformal parameterization are rectangles. Different reparameterization methods are utilized to optimize differential geometry properties of the freeform surfaces, and the superiority and disadvantage of different transformation methods are analyzed and compared. The future research trends of the surface parameterization are discussed. Examples are given to show the performance of different reparameterization algorithms for rendering and tessellation applications.

Assoc. Prof. Zongyong Cui

University of Electronic Science and Technology of China, China

Zongyong Cui, associate professor at the School of Information and Communication Engineering at UESTC. His research is about intelligent radar image interpretation, with a focus on the integration of SAR target detection and recognition, incremental learning, and SAR small sample target recognition. He has successively led scientific research projects from National Natural Science Foundation, National Defense Key Laboratory, and so on. He has published over 70 high-level papers and granted more than 20 national invention patents; Served as a reviewer for ISPRS Journal of Photography and Remote Sensing, IEEE TGRS, IEEE TAES, IEEE JSTAR, and other journals.