The field of visual computing is rapidly advancing due to the emergence of generative
artificial intelligence (AI), which unlocks unprecedented capabilities for the generation …

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

Though the advancement of pre-trained large language models unfolds, the exploration of
building a unified model for language and other multimodal data, such as motion, remains …

In recent times the generation of 3D assets from text prompts has shown impressive results.
Both 2D and 3D diffusion models can help generate decent 3D objects based on prompts …

In this paper, we present Motion-X, a large-scale 3D expressive whole-body motion dataset.
Existing motion datasets predominantly contain body-only poses, lacking facial expressions …

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 …

Human motion generation stands as a significant pursuit in generative computer vision,
while achieving long-sequence and efficient motion generation remains challenging. Recent …

We present an approach to modeling an image-space prior on scene motion. Our prior is
learned from a collection of motion trajectories extracted from real video sequences …

Denoising diffusion models have shown great promise in human motion synthesis
conditioned on natural language descriptions. However, integrating spatial constraints, such …

We present a novel alignment-before-generation approach to tackle the challenging task of
generating general 3D shapes based on 2D images or texts. Directly learning a conditional …