Recent diffusion model advancements have enabled high-fidelity images to be generated
using text prompts. However, a domain gap exists between generated images and real …

Shape and geometric patterns are essential in defining stylistic identity. However current 3D
style transfer methods predominantly focus on transferring colors and textures often …

Current 3D stylization methods often assume static scenes which violates the dynamic
nature of our real world. To address this limitation we present S-DyRF a reference-based …

We present our method for transferring style from any arbitrary image (s) to object (s) within a
3D scene. Our primary objective is to offer more control in 3D scene stylization, facilitating …

Due to the omnipresence of Neural Radiance Fields (NeRFs) the interest towards editable
implicit 3D representations has surged over the last years. However editing implicit or hybrid …

3D Gaussians have recently emerged as an efficient representation for novel view synthesis.
This work studies its editability with a particular focus on the inpainting task, which aims to …

While free-hand sketching has long served as an efficient representation to convey
characteristics of an object, they are often subjective, deviating significantly from realistic …

The radiance fields style transfer is an emerging field that has recently gained popularity as
a means of 3D scene stylization, thanks to the outstanding performance of neural radiance …

Neural radiance fields, which represent a 3D scene as a color field and a density field, have
demonstrated great progress in novel view synthesis yet are unfavorable for editing due to …

Modern artificial intelligence provides a novel way of producing digital art in styles. The
expressive power of neural networks enables the realm of visual style transfer methods …