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 …

In this work, we investigate a simple and must-known conditional generative framework
based on Vector Quantised-Variational AutoEncoder (VQ-VAE) and Generative Pre-trained …

Dance is an important human art form, but creating new dances can be difficult and time-
consuming. In this work, we introduce Editable Dance GEneration (EDGE), a state-of-the-art …

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 …

Driving 3D characters to dance following a piece of music is highly challenging due to the
spatial constraints applied to poses by choreography norms. In addition, the generated …

We present AIST++, a new multi-modal dataset of 3D dance motion and music, along with
FACT, a Full-Attention Cross-modal Transformer network for generating 3D dance motion …

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

Gestures are non-verbal but important behaviors accompanying people's speech. While
previous methods are able to generate speech rhythm-synchronized gestures, the semantic …

Generating controllable and editable human motion sequences is a key challenge in 3D
Avatar generation. It has been labor-intensive to generate and animate human motion for a …