Facial emotion recognition (FER) is a computer vision process aimed at detecting and
classifying human emotional expressions. FER systems are currently used in a vast range of …

The emergence of artificial emotional intelligence technology is revolutionizing the fields of
computers and robotics, allowing for a new level of communication and understanding of …

Abstract Context-Aware Emotion Recognition (CAER) is a crucial and challenging task that
aims to perceive the emotional states of the target person with contextual information …

Understanding emotion in context is a rising hotspot in the computer vision community.
Existing methods lack reliable context semantics to mitigate uncertainty in expressing …

Human multimodal emotion recognition involves time-series data of different modalities,
such as natural language, visual motions, and acoustic behaviors. Due to the variable …

Context-aware emotion recognition (CAER) has recently boosted the practical applications
of affective computing techniques in unconstrained environments. Mainstream CAER …

From sparse descriptions of events, observers can make systematic and nuanced
predictions of what emotions the people involved will experience. We propose a formal …

We present Text2Gestures, a transformer-based learning method to interactively generate
emotive full-body gestures for virtual agents aligned with natural language text inputs. Our …

Emotion understanding is an essential but highly challenging component of artificial general
intelligence. The absence of extensive annotated datasets has significantly impeded …

Abstract Multi-modal Multi-label Emotion Recognition (MMER) aims to identify various
human emotions from heterogeneous visual, audio and text modalities. Previous methods …