SS09: Graph Neural Networks for Multimedia Data Analysis
Motivation & significance
•showcase cutting-edge foundational theories, novel algorithms, and pioneering applications in graph/hypergraph learning, fostering collaboration and knowledge exchange between academia and industry.
•delve into theoretical advancements that enhance the expressiveness, generalization, and convergence properties of graph neural networks.
Topics of interest
•Image and Video Recognition
•Multimedia Recommendation Systems
•Cross-Modal Retrieval
•Content-Based Multimedia Analysis
•Social Media Analysis
•Graph Learning in Medical Image Analysis
Organizers
Shaoyi Du, Professor, Xi’an Jiaotong University, China, email: dushaoyi@xjtu.edu.cn
Shihui Ying, Professor, Shanghai University, China, email: shying@shu.edu.cn
Mingxia Liu, Assistant Professor, University of North Carolina at Chapel Hill, USA, email: mingxia_liu@med.unc.edu