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 …

Human motion generation aims to generate natural human pose sequences and shows
immense potential for real-world applications. Substantial progress has been made recently …

This work addresses the problem of generating 3D holistic body motions from human
speech. Given a speech recording, we synthesize sequences of 3D body poses, hand …

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 …

For human-like agents, including virtual avatars and social robots, making proper gestures
while speaking is crucial in human-agent interaction. Co-speech gestures enhance …

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 …

This paper reports on the second GENEA Challenge to benchmark data-driven automatic co-
speech gesture generation. Participating teams used the same speech and motion dataset …

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 …

Automatic gesture synthesis from speech is a topic that has attracted researchers for
applications in remote communication, video games and Metaverse. Learning the mapping …