In this system, we discuss methods to stylize a scene of 3D primitive objects into a higher fidelity 3D scene using novel 3D representations like NeRFs and 3D Gaussian Splatting. Our approach leverages existing image stylization systems and image-to-3D generative models to create a pipeline that iteratively stylizes and composites 3D objects into scenes. We show our results on adding generated objects into a scene and discuss limitations.

翻译：本文系统探讨了利用NeRF和三维高斯泼溅等新型三维表示方法，将基于图元的三维场景风格化为高保真三维场景的技术路径。我们通过整合现有图像风格化系统与图像到三维生成模型，构建了一个可迭代执行风格化与三维场景合成的处理流程。实验展示了生成物体在场景中的融合效果，并对当前方法的局限性进行了分析。