SemanticSplatStylization: Semantic Scene Stylization Based on 3D Gaussian Splatting and Class-based Style Transfer

We propose a novel approach for 3D Semantic Style Transfer in 3D Gaussian Splatting (3DGS) that applies style transfer to specific segments of a 3D scene using 2D style images. Our method leverages a finetuning of 3D Gaussian splats and fast 2D class-based style transfer to achieve targeted stylization with superior fidelity and multi-view consistency compared to existing state-of-the- art methods. By incorporating a semantic understanding, our approach ensures precise, context-aware stylization, aligning the visual characteristics of segments with their intended style. The application of 3D Semantic Style Transfer in cultural heritage preservation and restoration holds significant potential. By accurately capturing and transferring styles onto specific segments of cultural heritage objects, our approach demonstrates the potential of providing more accurate and visually appealing stylization results that preserve the integrity and historical significance of cultural heritage artifacts.