Neural Radiance Fields (NeRF) can be optimized to obtain high-fidelity 3...
Decomposing an object's appearance into representations of its materials...
Neural Radiance Fields (NeRFs) have emerged as a powerful neural 3D
repr...
Neural Radiance Field training can be accelerated through the use of
gri...
We present a method for reconstructing high-quality meshes of large unbo...
Neural radiance fields enable state-of-the-art photorealistic view synth...
Neural fields have emerged as a new paradigm for representing signals, t...
Humans form mental images of 3D scenes to support counterfactual imagina...
Neural Radiance Fields (NeRFs) are a powerful representation for modelin...
Recent breakthroughs in text-to-image synthesis have been driven by diff...
Inverse rendering of an object under entirely unknown capture conditions...
Thin, reflective objects such as forks and whisks are common in our dail...
We present Block-NeRF, a variant of Neural Radiance Fields that can repr...
We introduce a free-viewpoint rendering method – HumanNeRF – that works ...
We present squareplus, an activation function that resembles softplus, b...
Neural Radiance Fields (NeRF) is a popular view synthesis technique that...
Neural radiance fields (NeRF) encode a scene into a neural representatio...
We combine neural rendering with multi-modal image and text representati...
Neural Radiance Fields (NeRF) have emerged as a powerful representation ...
The goal of this work is to perform 3D reconstruction and novel view
syn...
Neural Radiance Fields (NeRF) is a technique for high quality novel view...
Though neural radiance fields (NeRF) have demonstrated impressive view
s...
Decomposing a scene into its shape, reflectance and illumination is a
fu...
We present a method that takes as input a single dual-pixel image, and
s...
We propose a deep generative model that performs typography analysis and...
Neural Radiance Fields (NeRF) are able to reconstruct scenes with
unprec...
We address the problem of recovering the shape and spatially-varying
ref...
Neural volumetric representations such as Neural Radiance Fields (NeRF) ...
The rendering procedure used by neural radiance fields (NeRF) samples a ...
We present a method that synthesizes novel views of complex scenes by
in...
We present iNeRF, a framework that performs pose estimation by "invertin...
We present a method that takes as input a set of images of a scene
illum...
Decomposing a scene into its shape, reflectance, and illumination is a
c...
Coordinate-based neural representations have shown significant promise a...
We present the first method capable of photorealistically reconstructing...
Lens flare is a common artifact in photographs occurring when the camera...
We present "Cross-Camera Convolutional Color Constancy" (C5), a
learning...
The light stage has been widely used in computer graphics for the past t...
We present a generalization of Schlick's bias and gain functions – simpl...
A fundamental problem in computer vision is that of inferring the intrin...
Traditional reflection removal algorithms either use a single image as i...
The light transport (LT) of a scene describes how it appears under diffe...
We present a learning-based method for synthesizing novel views of compl...
We present Generalized Histogram Thresholding (GHT), a simple, fast, and...
We show that passing input points through a simple Fourier feature mappi...
The sky is a major component of the appearance of a photograph, and its ...
We systematically compare and analyze a set of key components in unsuper...
Casually-taken portrait photographs often suffer from unflattering light...
Autofocus is an important task for digital cameras, yet current approach...
We present a method that achieves state-of-the-art results for synthesiz...