Abstract
Current 3D stylization techniques primarily focus on static scenes, while our world is inherently dynamic, filled with moving objects and changing environments. Existing style transfer methods primarily target appearance -- such as color and texture transformation -- but often neglect the geometric characteristics of the style image, which are crucial for achieving a complete and coherent stylization effect. To overcome these shortcomings, we propose GAS-NeRF, a novel approach for joint appearance and geometry stylization in dynamic Radiance Fields. Our method leverages depth maps to extract and transfer geometric details into the radiance field, followed by appearance transfer. Experimental results on synthetic and real-world datasets demonstrate that our approach significantly enhances the stylization quality while maintaining temporal coherence in dynamic scenes.
Abstract (translated)
当前的3D风格化技术主要集中在静态场景上，而我们的世界本质上是动态的，充满了移动的对象和不断变化的环境。现有的风格迁移方法主要关注外观的转换，如颜色和纹理的变化，但往往忽视了样式图像的几何特征，这对于实现完整且连贯的风格化效果至关重要。为了克服这些不足，我们提出了GAS-NeRF，这是一种新颖的方法，用于动态辐射场中的联合外观和几何风格化。我们的方法利用深度图来提取并传输几何细节到辐射场中，随后进行外观转换。在合成数据集和真实世界数据集上的实验结果表明，我们的方法显著提高了风格化的质量，并且在动态场景中保持了时间一致性。
URL
https://arxiv.org/abs/2503.08483
