Recently impressive results have been achieved in 3D scene editing with text instructions
based on a 2D diffusion model. However current diffusion models primarily generate images …

Abstract 3D style transfer aims to render stylized novel views of a 3D scene with multi-view
consistency. However, most existing work suffers from a three-way dilemma over accurate …

We present a method for transferring the artistic features of an arbitrary style image to a 3D
scene. Previous methods that perform 3D stylization on point clouds or meshes are sensitive …

Despite the great success in 2D editing using user-friendly tools, such as Photoshop,
semantic strokes, or even text prompts, similar capabilities in 3D areas are still limited, either …

As a powerful representation of 3D scenes, the neural radiance field (NeRF) enables high-
quality novel view synthesis from multi-view images. Stylizing NeRF, however, remains …

Abstract 3D scene stylization aims at generating stylized images of the scene from arbitrary
novel views following a given set of style examples, while ensuring consistency when …

Neural implicit fields are powerful for representing 3D scenes and generating high-quality
novel views, but it remains challenging to use such implicit representations for creating a 3D …

While text-3D editing has made significant strides in leveraging score distillation sampling,
emerging approaches still fall short in delivering separable, precise and consistent …

Abstract Neural Radiance Fields (NeRF) have the potential to be a major representation of
media. Since training a NeRF has never been an easy task, the protection of its model …

Abstract We introduce ViCA-NeRF, the first view-consistency-aware method for 3D editing
with text instructions. In addition to the implicit neural radiance field (NeRF) modeling, our …