Creating artistic 3D scenes can be time-consuming and requires specialized knowledge. To address this, recent works such as ARF, use a radiance field-based approach with style constraints to generate 3D scenes that resemble a style image provided by the user. However, these methods lack fine-grained control over the resulting scenes. In this paper, we introduce Controllable Artistic Radiance Fields (CoARF), a novel algorithm for controllable 3D scene stylization. CoARF enables style transfer for specified objects, compositional 3D style transfer and semantic-aware style transfer. We achieve controllability using segmentation masks with different label-dependent loss functions. We also propose a semantic-aware nearest neighbor matching algorithm to improve the style transfer quality. Our extensive experiments demonstrate that CoARF provides user-specified controllability of style transfer and superior style transfer quality with more precise feature matching.

翻译：创建艺术化的三维场景通常耗时且需要专业知识。为解决这一问题，近期研究如ARF采用基于辐射场的方法，结合风格约束生成与用户提供的风格图像相似的三维场景。然而，这些方法对生成场景缺乏细粒度的控制。本文提出可控艺术辐射场（CoARF），一种用于三维场景风格化的新型可控算法。CoARF实现了指定物体的风格迁移、组合式三维风格迁移及语义感知风格迁移。我们通过采用不同标签相关损失函数的分割掩码实现可控性，并提出一种语义感知的最近邻匹配算法以提升风格迁移质量。大量实验表明，CoARF提供了用户指定的风格迁移可控性，并通过更精准的特征匹配实现了更优的风格迁移质量。