This paper reviews the current state of the art in artificial intelligence (AI) technologies and
applications in the context of the creative industries. A brief background of AI, and …

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 …

We study a challenging task, conditional human motion generation, which produces
plausible human motion sequences according to various conditional inputs, such as action …

We introduce SceneDiffuser, a conditional generative model for 3D scene understanding.
SceneDiffuser provides a unified model for solving scene-conditioned generation …

Conventional methods for human motion synthesis have either been deterministic or have
had to struggle with the trade-off between motion diversity vs motion quality. In response to …

This paper addresses a novel task of anticipating 3D human-object interactions (HOIs). Most
existing research on HOI synthesis lacks comprehensive whole-body interactions with …

We tackle the problem of action-conditioned generation of realistic and diverse human
motion sequences. In contrast to methods that complete, or extend, motion sequences, this …

Inspired by the strong ties between vision and language, the two intimate human sensing
and communication modalities, our paper aims to explore the generation of 3D human full …

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 …