Neural Radiance Field (NeRF), a new novel view synthesis with implicit scene
representation has taken the field of Computer Vision by storm. As a novel view synthesis …

The emergence of 3D Gaussian splatting (3DGS) has greatly accelerated rendering in novel
view synthesis. Unlike neural implicit representations like neural radiance fields (NeRFs) …

Representing and rendering dynamic scenes has been an important but challenging task.
Especially to accurately model complex motions high efficiency is usually hard to guarantee …

We introduce k-planes, a white-box model for radiance fields in arbitrary dimensions. Our
model uses d-choose-2 planes to represent a d-dimensional scene, providing a seamless …

Modeling and re-rendering dynamic 3D scenes is a challenging task in 3D vision. Prior
approaches build on NeRF and rely on implicit representations. This is slow since it requires …

Automatic text-to-3D generation that combines Score Distillation Sampling (SDS) with the
optimization of volume rendering has achieved remarkable progress in synthesizing realistic …

We present TensoRF, a novel approach to model and reconstruct radiance fields. Unlike
NeRF that purely uses MLPs, we model the radiance field of a scene as a 4D tensor, which …

Emerging neural radiance fields (NeRF) are a promising scene representation for computer
graphics, enabling high-quality 3D reconstruction and novel view synthesis from image …

Implicit neural representation has paved the way for new approaches to dynamic scene
reconstruction. Nonetheless cutting-edge dynamic neural rendering methods rely heavily on …

We introduce a free-viewpoint rendering method--HumanNeRF--that works on a given
monocular video of a human performing complex body motions, eg a video from YouTube …