Multi-view stereo: A tutorial

Y Furukawa, C Hernández - Foundations and trends® in …, 2015‏ - nowpublishers.com
This tutorial presents a hands-on view of the field of multi-view stereo with a focus on
practical algorithms. Multi-view stereo algorithms are able to construct highly detailed 3D …

How to make sense of 3D representations for plant phenoty**: a compendium of processing and analysis techniques

N Harandi, B Vandenberghe, J Vankerschaver… - Plant Methods, 2023‏ - Springer
Computer vision technology is moving more and more towards a three-dimensional
approach, and plant phenoty** is following this trend. However, despite its potential, the …

Neuralangelo: High-fidelity neural surface reconstruction

Z Li, T Müller, A Evans, RH Taylor… - Proceedings of the …, 2023‏ - openaccess.thecvf.com
Neural surface reconstruction has been shown to be powerful for recovering dense 3D
surfaces via image-based neural rendering. However, current methods struggle to recover …

Neus2: Fast learning of neural implicit surfaces for multi-view reconstruction

Y Wang, Q Han, M Habermann… - Proceedings of the …, 2023‏ - openaccess.thecvf.com
Recent methods for neural surface representation and rendering, for example NeuS, have
demonstrated the remarkably high-quality reconstruction of static scenes. However, the …

Monosdf: Exploring monocular geometric cues for neural implicit surface reconstruction

Z Yu, S Peng, M Niemeyer, T Sattler… - Advances in neural …, 2022‏ - proceedings.neurips.cc
In recent years, neural implicit surface reconstruction methods have become popular for
multi-view 3D reconstruction. In contrast to traditional multi-view stereo methods, these …

Stylerf: Zero-shot 3d style transfer of neural radiance fields

K Liu, F Zhan, Y Chen, J Zhang, Y Yu… - Proceedings of the …, 2023‏ - openaccess.thecvf.com
Abstract 3D style transfer aims to render stylized novel views of a 3D scene with multi-view
consistency. However, most existing work suffers from a three-way dilemma over accurate …

Geo-neus: Geometry-consistent neural implicit surfaces learning for multi-view reconstruction

Q Fu, Q Xu, YS Ong, W Tao - Advances in Neural …, 2022‏ - proceedings.neurips.cc
Recently, neural implicit surfaces learning by volume rendering has become popular for
multi-view reconstruction. However, one key challenge remains: existing approaches lack …

Plenoxels: Radiance fields without neural networks

S Fridovich-Keil, A Yu, M Tancik… - Proceedings of the …, 2022‏ - openaccess.thecvf.com
We introduce Plenoxels (plenoptic voxels), a system for photorealistic view synthesis.
Plenoxels represent a scene as a sparse 3D grid with spherical harmonics. This …

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 …

Neus: Learning neural implicit surfaces by volume rendering for multi-view reconstruction

P Wang, L Liu, Y Liu, C Theobalt, T Komura… - arxiv preprint arxiv …, 2021‏ - arxiv.org
We present a novel neural surface reconstruction method, called NeuS, for reconstructing
objects and scenes with high fidelity from 2D image inputs. Existing neural surface …