With the advancement of virtual reality, the demand for 3D human avatars is increasing. The emergence of Gaussian Splatting technology has enabled the rendering of Gaussian avatars with superior visual quality and reduced computational costs. Despite numerous methods researchers propose for implementing drivable Gaussian avatars, limited attention has been given to balancing visual quality and computational costs. In this paper, we introduce LoDAvatar, a method that introduces levels of detail into Gaussian avatars through hierarchical embedding and selective detail enhancement methods. The key steps of LoDAvatar encompass data preparation, Gaussian embedding, Gaussian optimization, and selective detail enhancement. We conducted experiments involving Gaussian avatars at various levels of detail, employing both objective assessments and subjective evaluations. The outcomes indicate that incorporating levels of detail into Gaussian avatars can decrease computational costs during rendering while upholding commendable visual quality, thereby enhancing runtime frame rates. We advocate adopting LoDAvatar to render multiple dynamic Gaussian avatars or extensive Gaussian scenes to balance visual quality and computational costs.

翻译：随着虚拟现实技术的发展，对三维人体化身的需求日益增长。高斯溅射技术的出现使得高斯化身的渲染在视觉质量上更优且计算成本更低。尽管研究人员提出了多种实现可驱动高斯化身的方法，但在平衡视觉质量与计算成本方面的关注仍显不足。本文提出LoDAvatar，一种通过分层嵌入和选择性细节增强方法为高斯化身引入细节层级的技术。LoDAvatar的关键步骤包括数据准备、高斯嵌入、高斯优化以及选择性细节增强。我们通过客观评估与主观评价相结合的方式，对不同细节层级的高斯化身进行了实验。结果表明，在高斯化身中引入细节层级能够在保持良好视觉质量的同时降低渲染过程中的计算成本，从而提高运行时帧率。我们建议采用LoDAvatar来渲染多个动态高斯化身或大规模高斯场景，以实现视觉质量与计算成本之间的平衡。