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Nerfstudio: A Modular Framework for Neural Radiance Field Development

Authors:

Matthew Tancik,

Alexander Kristoffersen,

David Mcallister,

Angjoo KanazawaAuthors Info & Claims

SIGGRAPH '23: ACM SIGGRAPH 2023 Conference Proceedings

Article No.: 72, Pages 1 - 12

https://doi.org/10.1145/3588432.3591516

Published: 23 July 2023 Publication History

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Abstract

Neural Radiance Fields (NeRF) are a rapidly growing area of research with wide-ranging applications in computer vision, graphics, robotics, and more. In order to streamline the development and deployment of NeRF research, we propose a modular PyTorch framework, Nerfstudio. Our framework includes plug-and-play components for implementing NeRF-based methods, which make it easy for researchers and practitioners to incorporate NeRF into their projects. Additionally, the modular design enables support for extensive real-time visualization tools, streamlined pipelines for importing captured in-the-wild data, and tools for exporting to video, point cloud and mesh representations. The modularity of Nerfstudio enables the development of Nerfacto, our method that combines components from recent papers to achieve a balance between speed and quality, while also remaining flexible to future modifications. To promote community-driven development, all associated code and data are made publicly available with open-source licensing.

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https://doi.org/10.4018/IJIIT.369336
Rangelov DWaanders SWaanders KKeulen MMiltchev R(2025)Impact of Data Capture Methods on 3D Reconstruction with Gaussian SplattingJournal of Imaging10.3390/jimaging1102006511:2(65)Online publication date: 18-Feb-2025
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Korycki AYeaton CGilbert GJosephson CMcGuire S(2025)NeRF-Accelerated Ecological Monitoring in Mixed-Evergreen Redwood ForestForests10.3390/f1601017316:1(173)Online publication date: 17-Jan-2025
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Index Terms

Nerfstudio: A Modular Framework for Neural Radiance Field Development
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Reconstruction
  2. Computer graphics

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cover image ACM Conferences

SIGGRAPH '23: ACM SIGGRAPH 2023 Conference Proceedings

July 2023

911 pages

ISBN:9798400701597

DOI:10.1145/3588432

Copyright © 2023 Owner/Author.

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Published: 23 July 2023

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