Abstract Neural Radiance Fields (NeRFs) have emerged as a popular approach for novel
view synthesis. While NeRFs are quickly being adapted for a wider set of applications …

As information exists in various modalities in real world, effective interaction and fusion
among multimodal information plays a key role for the creation and perception of multimodal …

As information exists in various modalities in real world, effective interaction and fusion
among multimodal information plays a key role for the creation and perception of multimodal …

We propose NeRFiller an approach that completes missing portions of a 3D capture via
generative 3D inpainting using off-the-shelf 2D visual generative models. Often parts of a …

In recent years, Neural Radiance Fields (NeRF) has made remarkable progress in the field
of computer vision and graphics, providing strong technical support for solving key tasks …

Neural Radiance Field (NeRF) has achieved substantial progress in novel view synthesis
given multi-view images. Recently, some works have attempted to train a NeRF from a …

We consider the problem of editing 3D objects and scenes based on open-ended language
instructions. A common approach to this problem is to use a 2D image generator or editor to …

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 …

We show that physics-based simulations can be seamlessly integrated with NeRF to
generate high-quality elastodynamics of real-world objects. Unlike existing methods we …

We propose a novel feed-forward 3D editing framework called Shap-Editor. Prior research
on editing 3D objects primarily concentrated on editing individual objects by leveraging off …