nerfstudio

Nerfstudio is an open-source radiance field framework that began at UC Berkeley in Angjoo Kanazawa's lab, released under the Apache 2.0 license. Matthew Tancik, Ethan Weber and Evonne Ng lead the author list of the framework paper, which the team presented at SIGGRAPH 2023.

Their goal is to create a user-friendly experience to explore radiance fields and be a contributor-friendly repo to build a community where users can easily build upon each other’s contributions.

Nerfstudio quickly expanded to become one of the most popular models to utilize, with both companies such as Polycam using it, in addition to researchers.

Nerfstudio is sponsored by both Luma AI and Berkeley Artificial Intelligence Research (BAIR).

Supported Radiance Field methods on Nerfstudio

While Nerfstudio originally launched for NeRFs, it was because at the time NeRFs were the only existing Radiance Field method. With the creation of 3D Gaussian Splatting, Nerfstudio has since expanded their offering to also include their homemade implementation, Splatfacto.

Over time the number of methods that Nerfstudio offers has continued to grow. The latest tagged release is v1.1.5, published to GitHub and PyPI on November 11, 2024, following v1.1 in May 2024. Commits have continued on the main branch since, most recently on July 29, 2025, and are not in a tagged release. Both the release and the main branch pin gsplat 1.4.0, while gsplat itself reached version 1.5.3 on July 4, 2025.

Implemented Methods

The following methods are supported in Nerfstudio:

• BioNeRF: Biologically Plausible Neural Radiance Fields for View Synthesis

• Instant NGP: Instant Neural Graphics Primitives with a Multi Resolution Hash Encoding

• Instruct-GS2GS: Editing Gaussian Splatting Scenes with Instructions

• Instruct-NeRF2NeRF: Editing 3D Scenes with Instructions

• Generfacto: Generate 3D models from text

• K-Planes: Unified 3D and 4D Radiance Fields

• LERF: Language Embedded Radiance Fields

• Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fields

• NeRF: The original NeRF paper.

• Nerfacto: our de facto NeRF method combines modules focused on quality with modules focused on faster rendering. nerfstudio easily lets us experiment with the best of both worlds! There is also Nerfacto-Big and Nerfacto-Huge, which are more powerful and VRAM consuming methods.

• Nerfbusters: Removing Ghostly Artifacts from Casually Captured NeRFs

• NeRFPlayer: A Streamable Dynamic Scene Representation with Decomposed Neural Radiance Fields

• NeRFtoGSandBack: From NeRFs to Gaussian Splats, and Back

• OpenNeRF: OpenSet 3D Neural Scene Segmentation with Pixel-wise Features and Rendered Novel Views

• PyNeRF: Pyramidal Neural Radiance Fields for fast NeRF anti-aliasing.

• Tetra-NeRF: Representing Neural Radiance Fields Using Tetrahedra

• TensoRF: Tensorial Radiance Fields

• Splatfacto: Nerfstudio's homemade implementation of 3D Gaussian Splatting. It rasterizes through gsplat, the CUDA library the Nerfstudio team maintains, and exports trained splats as .ply files. The docs list Splatfacto at about 6 GB of VRAM and Splatfacto-Big, with more Gaussians and higher quality, at about 12 GB. A Splatfacto-MCMC configuration using the 3DGS MCMC densification strategy exists on the main branch but is not in the v1.1.5 release.

• SeaThru-NeRF: A NeRF method targeting underwater, foggy, or hazy scenes.

• Zip-NeRF: Google's SoTA method.

• Splatfacto-W: Splatfacto in the Wild, Gaussian Splatting for unconstrained photo collections

• SIGNeRF: Scene Integrated Generation for Neural Radiance Fields

• Feature Splatting: distills SAM-enhanced CLIP features into 3D Gaussian Splatting for segmentation and editing

• LiveScene: Language Embedding Interactive Radiance Fields for Physical Scene Rendering and Control

Nerfstudio also allows you to submit your own methods, but it must be in their format. They have provided documentation on how to do so, here.

After the method is properly formatted, you need to follow these steps:

Add a markdown file describing the model to the docs/nerfology/methods folder

1. Update the above list of implement methods in this file.

2. Add the method to this list in docs/index.md.

3. Add a new ExternalMethod entry to the nerfstudio/configs/external_methods.py file.

Nerfstudio Extensions

There have been the following extensions created for Nerfstudio

• A Blender VFX add-on

  

• Unreal Engine exporting, through Volinga's NVOL format, converted from Nerfacto-based Volinga model checkpoints

• An Autodesk Maya plug-in that writes a shared camera path so Nerfacto renders can be composited with Maya animation

• SDFStudio

Nerfstudio Viewer

Nerfstudio additionally has its own real time web viewer, Viser, which doesn't require any installation and allows you to view your training process on the device. Additionally, the Viser viewer now allows users to generate a share link to a capture, but it will still run on your local machine. Viser can also be modified into a custom GUI using the linked documentation.

The viewer is built on Viser using ThreeJS and packaged into a ReactJS application. This client viewer application will connect via a websocket to a server running on your machine. If you prefer to use the legacy viewer, Nerfstudio still supports using it.

Nerfstudio Tutorials

There are some great tutorials on YouTube on how to set up and use Nerfstudio. Check out some of the content created by Jonathan Stephens, the NeRFGuru