Neural Stylization

Neural stylization aims to transfer the artistic style of an image or text prompt onto 3D scenes or meshes, creating visually appealing and consistent results across different viewpoints. Current research focuses on developing methods that leverage neural radiance fields (NeRFs), implicit neural representations, and mesh-based approaches, often incorporating techniques like frequency decomposition and prompt-based style mapping to achieve high-fidelity and transferable stylization. These advancements are improving the realism and efficiency of 3D content creation for applications such as medical visualization, animation, and artistic expression, bridging the gap between 2D image stylization and the complexities of 3D scene manipulation. The ability to control and manipulate the style of 3D models offers significant potential for various fields.