GAS-NeRF: Geometry-Aware Stylization of Dynamic Radiance Fields
Journal:
arXiv
Published Date:
Mar 11, 2025
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.
