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 …

We present a generative adversarial network to synthesize 3D pose sequences of co-
speech upper-body gestures with appropriate affective expressions. Our network consists of …

We present a novel classifier network called STEP, to classify perceived human emotion
from gaits, based on a Spatial Temporal Graph Convolutional Network (ST-GCN) …

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 …

We present ProxEmo, a novel end-to-end emotion prediction algorithm for socially aware
robot navigation among pedestrians. Our approach predicts the perceived emotions of a …

Emotions can be perceived from a person's gait, ie, their walking style. Existing methods on
gait emotion recognition mainly leverage the posture information as input, but ignore the …

Emotion recognition in-the-wild under uncontrolled conditions is a challenge, because facial
expression is often blurred or even missing in the public space, while the previous visual …

Psychological trait estimation from external factors such as movement and appearance is a
challenging and long-standing problem in psychology, and is principally based on the …

Motion capture sensor-based gait emotion recognition is an emerging sub-domain of human
emotion recognition. Its applications span a variety of fields including smart home design …

This paper focuses on contrastive learning for gait-based emotion recognition. The existing
contrastive learning approaches are rarely suitable for learning skeleton-based gait …