State of the art on neural rendering

A Tewari, O Fried, J Thies, V Sitzmann… - Computer Graphics …, 2020 - Wiley Online Library
Efficient rendering of photo‐realistic virtual worlds is a long standing effort of computer
graphics. Modern graphics techniques have succeeded in synthesizing photo‐realistic …

Extracting triangular 3d models, materials, and lighting from images

J Munkberg, J Hasselgren, T Shen… - Proceedings of the …, 2022 - openaccess.thecvf.com
We present an efficient method for joint optimization of topology, materials and lighting from
multi-view image observations. Unlike recent multi-view reconstruction approaches, which …

Nerfactor: Neural factorization of shape and reflectance under an unknown illumination

X Zhang, PP Srinivasan, B Deng, P Debevec… - ACM Transactions on …, 2021 - dl.acm.org
We address the problem of recovering the shape and spatially-varying reflectance of an
object from multi-view images (and their camera poses) of an object illuminated by one …

Nerv: Neural reflectance and visibility fields for relighting and view synthesis

PP Srinivasan, B Deng, X Zhang… - Proceedings of the …, 2021 - openaccess.thecvf.com
We present a method that takes as input a set of images of a scene illuminated by
unconstrained known lighting, and produces as output a 3D representation that can be …

Nerd: Neural reflectance decomposition from image collections

M Boss, R Braun, V Jampani… - Proceedings of the …, 2021 - openaccess.thecvf.com
Decomposing a scene into its shape, reflectance, and illumination is a challenging but
important problem in computer vision and graphics. This problem is inherently more …

Tensoir: Tensorial inverse rendering

H Jin, I Liu, P Xu, X Zhang, S Han… - Proceedings of the …, 2023 - openaccess.thecvf.com
We propose TensoIR, a novel inverse rendering approach based on tensor factorization and
neural fields. Unlike previous works that use purely MLP-based neural fields, thus suffering …

Physg: Inverse rendering with spherical gaussians for physics-based material editing and relighting

K Zhang, F Luan, Q Wang, K Bala… - Proceedings of the …, 2021 - openaccess.thecvf.com
We present an end-to-end inverse rendering pipeline that includes a fully differentiable
renderer, and can reconstruct geometry, materials, and illumination from scratch from a set …

Neural-pil: Neural pre-integrated lighting for reflectance decomposition

M Boss, V Jampani, R Braun, C Liu… - Advances in …, 2021 - proceedings.neurips.cc
Decomposing a scene into its shape, reflectance and illumination is a fundamental problem
in computer vision and graphics. Neural approaches such as NeRF have achieved …

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 …

Neural fields meet explicit geometric representations for inverse rendering of urban scenes

Z Wang, T Shen, J Gao, S Huang… - Proceedings of the …, 2023 - openaccess.thecvf.com
Reconstruction and intrinsic decomposition of scenes from captured imagery would enable
many applications such as relighting and virtual object insertion. Recent NeRF based …