论文标题
Ref-NPR：基于参考的非遗迹辐射场，用于可控场景风格
Ref-NPR: Reference-Based Non-Photorealistic Radiance Fields for Controllable Scene Stylization
论文作者
论文摘要
当前的3D场景样式方法使用任意样式参考将纹理和颜色作为样式传递，缺乏有意义的语义对应关系。我们介绍了基于参考的非遗迹辐射场（REF-NPR）来解决此限制。这种可控的方法使用带有单个风格的2D视图作为参考的Radiance字段对3D场景进行风格化。我们提出了一个基于风格的参考视图的射线注册过程，以在新型视图中获得伪射线监督。然后，我们利用内容图像中的语义对应关系来填充具有相似风格的遮挡区域，从而导致非遗迹和连续的新型视图序列。我们的实验结果表明，Ref-NPR的表现优于现有场景和有关视觉质量和语义对应的视频风格化方法。代码和数据在项目页面上可公开可用，网址为https://ref-npr.github.io。
Current 3D scene stylization methods transfer textures and colors as styles using arbitrary style references, lacking meaningful semantic correspondences. We introduce Reference-Based Non-Photorealistic Radiance Fields (Ref-NPR) to address this limitation. This controllable method stylizes a 3D scene using radiance fields with a single stylized 2D view as a reference. We propose a ray registration process based on the stylized reference view to obtain pseudo-ray supervision in novel views. Then we exploit semantic correspondences in content images to fill occluded regions with perceptually similar styles, resulting in non-photorealistic and continuous novel view sequences. Our experimental results demonstrate that Ref-NPR outperforms existing scene and video stylization methods regarding visual quality and semantic correspondence. The code and data are publicly available on the project page at https://ref-npr.github.io.
