Decoupling the illumination in 3D scenes is crucial for novel view synthesis
and relighting. In this paper, we propose a novel method for representing a
scene illuminated by a point light using a set of relightable 3D Gaussian
points. Inspired by the Blinn-Phong model, our approach decomposes the scene
into ambient, diffuse, and specular components, enabling the synthesis of
realistic lighting effects. To facilitate the decomposition of geometric
information independent of lighting conditions, we introduce a novel bilevel
optimization-based meta-learning framework. The fundamental idea is to view the
rendering tasks under various lighting positions as a multi-task learning
problem, which our meta-learning approach effectively addresses by generalizing
the learned Gaussian geometries not only across different viewpoints but also
across diverse light positions. Experimental results demonstrate the
effectiveness of our approach in terms of training efficiency and rendering
quality compared to existing methods for free-viewpoint relighting.

在本文中，我们通过使用一组可重新照明的 3D 高斯点来表示点光源照亮的场景，提出了一种新方法。受到 Blinn-Phong 模型的启发，我们的方法将场景分解为环境、漫反射和镜面三个组成部分，实现了逼真的照明效果合成。为了促进与光照条件无关的几何信息的分解，我们引入了一种基于双层优化的元学习框架。基本思想是将各个光照位置下的渲染任务视为多任务学习问题，我们的元学习方法通过在不同视点和不同光照位置中泛化学习到的高斯几何形状，有效地解决了这一问题。实验证明，与现有的自由视点重新照明方法相比，我们的方法在训练效率和渲染质量方面具有较高的效果。