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 …

Abstract 3D human motion generation is crucial for creative industry. Recent advances rely
on generative models with domain knowledge for text-driven motion generation, leading to …

Recent work has demonstrated the significant potential of denoising diffusion models for
generating human motion, including text-to-motion capabilities. However, these methods are …

Abstract We present\emph {DreamHuman}, a method to generate realistic animatable 3D
human avatar models entirely from textual descriptions. Recent text-to-3D methods have …

This work introduces MotionLCM, extending controllable motion generation to a real-time
level. Existing methods for spatial-temporal control in text-conditioned motion generation …

We have recently seen tremendous progress in diffusion advances for generating realistic
human motions. Yet, they largely disregard the multi-human interactions. In this paper, we …

In this paper, we present TMR, a simple yet effective approach for text to 3D human motion
retrieval. While previous work has only treated retrieval as a proxy evaluation metric, we …

Our goal is to synthesize 3D human motions given textual inputs describing simultaneous
actions, for examplewaving hand'whilewalking'at the same time. We refer to generating such …

Large-scale pre-trained Vision & Language (VL) models have shown remarkable
performance in many applications, enabling replacing a fixed set of supported classes with …