Abstract
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.
Abstract (translated)
创建艺术化的3D场景可能需要花费时间,并且需要专业知识。为了解决这个问题,最近的工作如ARF,采用基于辐射场的方法,带有风格约束,从用户提供的风格图像中生成类似于用户风格的3D场景。然而,这些方法缺乏对生成场景的细粒度控制。在本文中,我们介绍了可控制的艺术化辐射场(CoARF),一种用于可控制3D场景的风格化的新算法。CoARF允许指定对象的样式转移、合成3D样式转移和语义感知样式转移。我们通过具有不同标签相关损失函数的分割掩码实现可控性。我们还提出了一个语义感知最近邻匹配算法,以提高样式转移质量。我们广泛的实验证明,CoARF提供了用户指定风格转移的可控性和卓越的样式转移质量,具有更精确的特征匹配。
URL
https://arxiv.org/abs/2404.14967
