This topic involves creating virtual agents (digital human)
that can simulate and replicate multi-modal human-style behavioural verbal and non-verbal
reactions in response to various external stimulus during human-computer interactions.
Siyang Song*#, Micol Spitale, Cheng Luo#, Hengde Zhu, German Barquero, Cristina Palmero, Sergio Escalera, Michel Valstar, Tobias Baur, Fabien Ringeval, Elisabeth André, and Hatice Gunes
This topic creates multi-modal machine learning
systyems that can efficiently, objectively, accurately and automatically
assess human personality traits and internal mental health status from
human long-term behaviours.
Facial expression, identity and emotion recognition
This topic create multi-modal machine learning
systyems that can efficiently, objectively, accurately and automatically
identify image-level human identities (i.e., face recognition), facial
expressions, emotions and even multiple facial muscle activations (i.e., Action Units).
This topic focuses on developing various graph representation
learning algorithms to convert image, video, audio and other data into graphs with multi-dimensional
edge features, as well as various novel GNNs whose nodes can represent matrices or graphs.