MoDiTalker: Motion-Disentangled Diffusion Model for High-Fidelity Talking Head Generation

arXiv:2403.19144v1 Announce Type: new
Abstract: Conventional GAN-based models for talking head generation often suffer from limited quality and unstable training. Recent approaches based on diffusion models aimed to address these limitations and improve fidelity. However, they still face challenges, including extensive sampling times and difficulties in maintaining temporal consistency due to the high stochasticity of diffusion models. To overcome these challenges, we propose a novel motion-disentangled diffusion model for high-quality talking head generation, dubbed MoDiTalker. We introduce the two modules: …

abstract arxiv challenges cs.cv diffusion diffusion model diffusion models face fidelity gan head however limitations quality sampling talking head temporal training type