Gestures that accompany speech are an essential part of natural and efficient embodied
human communication. The automatic generation of such co‐speech gestures is a long …

Sight and hearing are two senses that play a vital role in human communication and scene
understanding. To mimic human perception ability, audio-visual learning, aimed at …

Diffusion models have experienced a surge of interest as highly expressive yet efficiently
trainable probabilistic models. We show that these models are an excellent fit for …

Automatic synthesis of realistic co-speech gestures is an increasingly important yet
challenging task in artificial embodied agent creation. Previous systems mainly focus on …

Generating speech-consistent body and gesture movements is a long-standing problem in
virtual avatar creation. Previous studies often synthesize pose movement in a holistic …

Automatic synthesis of realistic gestures promises to transform the fields of animation,
avatars and communicative agents. In off‐line applications, novel tools can alter the role of …

Data-driven modelling and synthesis of motion is an active research area with applications
that include animation, games, and social robotics. This paper introduces a new class of …

Recent deep learning-based approaches have shown promising results for synthesizing
plausible 3D human gestures from speech input. However, these approaches typically offer …

Co-speech gesture is crucial for human-machine interaction and digital entertainment. While
previous works mostly map speech audio to human skeletons (eg, 2D keypoints), directly …

How can we teach robots or virtual assistants to gesture naturally? Can we go further and
adapt the gesturing style to follow a specific speaker? Gestures that are naturally timed with …