We propose the Unified Transformer for Facial Reaction GeneratioN (UniFaRN) framework
for facial reaction prediction in dyadic interactions. Given the video and audio of one side …

The Multiple Appropriate Facial Reaction Generation Challenge (REACT2023) is the first
competition event focused on evaluating multimedia processing and machine learning …

Offline Multiple Appropriate Facial Reaction Generation (OMAFRG) aims to predict the
reaction of different listeners given a speaker, which is useful in the senario of human …

In dyadic interactions, humans communicate their intentions and state of mind using verbal
and non-verbal cues, where multiple different facial reactions might be appropriate in …

This paper presents a framework for generating appropriate facial expressions for a listener
engaged in a dyadic conversation. The ability to produce contextually suitable facial …

Human facial reactions play crucial roles in dyadic human-human interactions, where
individuals (ie, listeners) with varying cognitive process styles may display different but …

In the realm of dyadic interactions, the ability to generate appropriate facial reactions is
paramount for the conveyance of empathy and understanding. This paper introduces a …

As autonomous interactive agents become increasingly prevalent, it is crucial for these
virtual agents to understand and respond to both our verbal content and emotions, enabling …

Facial reaction generation has gained prominence in recent years. However, while there
has been extensive research on synthesizing facial expressions from the perspective of the …

Creating a human-like interface in human-robot interaction is a formidable challenge. Many
efforts have been made to mimic the human ability of attentive listening and synchronous …