AnimateMe: 4D Facial Expressions via Diffusion Models

arXiv:2403.17213v1 Announce Type: new
Abstract: The field of photorealistic 3D avatar reconstruction and generation has garnered significant attention in recent years; however, animating such avatars remains challenging. Recent advances in diffusion models have notably enhanced the capabilities of generative models in 2D animation. In this work, we directly utilize these models within the 3D domain to achieve controllable and high-fidelity 4D facial animation. By integrating the strengths of diffusion processes and geometric deep learning, we employ Graph Neural Networks (GNNs) …

abstract advances animation arxiv attention avatar avatars capabilities cs.cv diffusion diffusion models generative generative models however photorealistic type via work