NTIRE 2023 challenge on efficient super-resolution: Methods and results
This paper reviews the NTIRE 2023 challenge on efficient single-image super-resolution
with a focus on the proposed solutions and results. The aim of this challenge is to devise a …
with a focus on the proposed solutions and results. The aim of this challenge is to devise a …
State of the art on neural rendering
Efficient rendering of photo‐realistic virtual worlds is a long standing effort of computer
graphics. Modern graphics techniques have succeeded in synthesizing photo‐realistic …
graphics. Modern graphics techniques have succeeded in synthesizing photo‐realistic …
Advances in neural rendering
Synthesizing photo‐realistic images and videos is at the heart of computer graphics and has
been the focus of decades of research. Traditionally, synthetic images of a scene are …
been the focus of decades of research. Traditionally, synthetic images of a scene are …
Shape, light, and material decomposition from images using monte carlo rendering and denoising
J Hasselgren, N Hofmann… - Advances in Neural …, 2022 - proceedings.neurips.cc
Recent advances in differentiable rendering have enabled high-quality reconstruction of 3D
scenes from multi-view images. Most methods rely on simple rendering algorithms: pre …
scenes from multi-view images. Most methods rely on simple rendering algorithms: pre …
A point-cloud deep learning framework for prediction of fluid flow fields on irregular geometries
We present a novel deep learning framework for flow field predictions in irregular domains
when the solution is a function of the geometry of either the domain or objects inside the …
when the solution is a function of the geometry of either the domain or objects inside the …
tempogan: A temporally coherent, volumetric gan for super-resolution fluid flow
We propose a temporally coherent generative model addressing the super-resolution
problem for fluid flows. Our work represents a first approach to synthesize four-dimensional …
problem for fluid flows. Our work represents a first approach to synthesize four-dimensional …
Geometry processing with neural fields
Most existing geometry processing algorithms use meshes as the default shape
representation. Manipulating meshes, however, requires one to maintain high quality in the …
representation. Manipulating meshes, however, requires one to maintain high quality in the …
[PDF][PDF] Kernel-predicting convolutional networks for denoising Monte Carlo renderings.
Kernel-Predicting Convolutional Networks for Denoising Monte Carlo Renderings Page 1
Kernel-Predicting Convolutional Networks for Denoising Monte Carlo Renderings STEVE …
Kernel-Predicting Convolutional Networks for Denoising Monte Carlo Renderings STEVE …
Physics and AI-based digital twin of multi-spectrum propagation characteristics for communication and sensing in 6G and beyond
To realize intelligent connection of everything and the digital twin (DT) of the physical world
in 6G and beyond, new communication and sensing solutions are demanded. The potential …
in 6G and beyond, new communication and sensing solutions are demanded. The potential …
Expandnet: A deep convolutional neural network for high dynamic range expansion from low dynamic range content
D Marnerides, T Bashford‐Rogers… - Computer Graphics …, 2018 - Wiley Online Library
High dynamic range (HDR) imaging provides the capability of handling real world lighting as
opposed to the traditional low dynamic range (LDR) which struggles to accurately represent …
opposed to the traditional low dynamic range (LDR) which struggles to accurately represent …