Abstract We introduce Efficient Motion Diffusion Model (EMDM) for fast and high-quality
human motion generation. Current state-of-the-art generative diffusion models have …

In this paper, we introduce an innovative task focused on human communication, aiming to
generate 3D holistic human motions for both speakers and listeners. Central to our …

Audio-driven 3D facial animation aims to map input audio to realistic facial motion. Despite
significant progress, limitations arise from inconsistent 3D annotations, restricting previous …

Human pose plays a crucial role in the digital age. While recent works have achieved
impressive progress in understanding and generating human poses, they often support only …

The evolution of computational intelligence, especially deep learning, has revolutionized
problem-solving approaches, with human pose estimation emerging as a popular challenge …

Estimating 3D human poses from monocular images is an important research area with
many practical applications. However, the depth ambiguity of 2D solutions limits their …

We propose a one-stage framework for real-time multi-person 3D human mesh estimation
from a single RGB image. While current one-stage methods, which follow a DETR-style …

Single-image human mesh recovery is a challenging task due to the ill-posed nature of
simultaneous body shape, pose, and camera estimation. Existing estimators work well on …

Simulating long-term human-scene interaction is a challenging yet fascinating task. Previous
works have not effectively addressed the generation of long-term human scene interactions …

In practical applications of human pose estimation, low-resolution inputs frequently occur,
and existing state-of-the-art models perform poorly with low-resolution images. This work …