Despite the emergence of successful NeRF inpainting methods built upon explicit RGB and
depth 2D inpainting supervisions these methods are inherently constrained by the …

We present GenN2N a unified NeRF-to-NeRF translation framework for various NeRF
translation tasks such as text-driven NeRF editing colorization super-resolution inpainting …

Recently, 3D Gaussian, as an explicit 3D representation method, has demonstrated strong
competitiveness over NeRF (Neural Radiance Fields) in terms of expressing complex …

Abstract Neural Radiance Field (NeRF) has been widely recognized for its excellence in
novel view synthesis and 3D scene reconstruction. However their effectiveness is inherently …

Abstract Extensions of Neural Radiance Fields (NeRFs) to model dynamic scenes have
enabled their near photo-realistic free-viewpoint rendering. Although these methods have …

Recently, advances in differential volumetric rendering enabled significant breakthroughs in
the photo-realistic and fine-detailed reconstruction of complex 3D scenes, which is key for …

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 …

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 …

Training perception systems for self-driving cars requires substantial annotations. However,
manual labeling in 2D images is highly labor-intensive. While existing datasets provide rich …

Addressing the intricate challenge of modeling and re-rendering dynamic scenes most
recent approaches have sought to simplify these complexities using plane-based explicit …