Methods¶
Zip-NeRF¶
CamP: Camera Preconditioning for Neural Radiance Fields
- Authors:
- Keunhong Park, Philipp Henzler, Ben Mildenhall, Jonathan T. Barron, Ricardo Martin-Brualla
- Paper:
- Web:
- ID:
- camp
CamP is an extension of Zip-NeRF which adds pose refinement to the training process.
Gaussian Splatting¶
3D Gaussian Splatting for Real-Time Radiance Field Rendering
- Authors:
- Bernhard Kerbl, Georgios Kopanas, Thomas Leimkühler, George Drettakis
- Paper:
https://repo-sam.inria.fr/fungraph/3d-gaussian-splatting/3d_gaussian_splatting_low.pdf
- Web:
- ID:
- gaussian-splatting
Official Gaussian Splatting implementation extended to support distorted camera models. It is fast to train (1 hous) and render (200 FPS).
Instant NGP¶
Instant Neural Graphics Primitives with a Multiresolution Hash Encoding
- Authors:
- Thomas Müller, Alex Evans, Christoph Schied, Alexander Keller
- Paper:
https://nvlabs.github.io/instant-ngp/assets/mueller2022instant.pdf
- Web:
- ID:
- instant-ngp
Instant-NGP is a method that uses hash-grid and a shallow MLP to accelerate training and rendering. This method trains very fast (~6 min) and renders also fast ~3 FPS.
Mip-Splatting¶
Mip-Splatting: Alias-free 3D Gaussian Splatting
- Authors:
- Zehao Yu, Anpei Chen, Binbin Huang, Torsten Sattler, Andreas Geiger
- Paper:
- Web:
- ID:
- mip-splatting
A modification of Gaussian Splatting designed to better handle aliasing artifacts.
Mip-NeRF 360¶
Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fields
- Authors:
- Jonathan T. Barron, Ben Mildenhall, Dor Verbin, Pratul P. Srinivasan, Peter Hedman
- Paper:
- Web:
- ID:
- mipnerf360
Official Mip-NeRF 360 implementation addapted to handle different camera distortion/intrinsic parameters. It was designed for unbounded object-centric 360-degree capture and handles anti-aliasing well. It is, however slower to train and render compared to other approaches.
NerfStudio¶
Nerfstudio: A Modular Framework for Neural Radiance Field Development
- Authors:
- Matthew Tancik, Ethan Weber, Evonne Ng, Ruilong Li, Brent Yi, Justin Kerr, Terrance Wang, Alexander Kristoffersen, Jake Austin, Kamyar Salahi, Abhik Ahuja, David McAllister, Angjoo Kanazawa
- Paper:
- Web:
- ID:
- nerfacto
NerfStudio (Nerfacto) is a method based on Instant-NGP which combines several improvements from different papers to achieve good quality on real-world scenes captured under normal conditions. It is fast to train (12 min) and render speed is ~1 FPS.
TensoRF¶
TensoRF: Tensorial Radiance Fields
- Authors:
- Anpei Chen, Zexiang Xu, Andreas Geiger, Jingyi Yu, Hao Su
- Paper:
- Web:
- ID:
- tensorf
TensoRF factorizes the radiance field into a multiple compact low-rank tensor components. It was designed and tester primarily on Blender, LLFF, and NSVF datasets.
Tetra-NeRF¶
Tetra-NeRF: Representing Neural Radiance Fields Using Tetrahedra
- Authors:
- Jonas Kulhanek, Torsten Sattler
- Paper:
- Web:
- ID:
- tetra-nerf
Tetra-NeRF is a method that represents the scene as tetrahedral mesh obtained using Delaunay tetrahedralization. The input point cloud has to be provided (for COLMAP datasets the point cloud is automatically extracted). This is the official implementation from the paper.
Zip-NeRF¶
Zip-NeRF: Anti-Aliased Grid-Based Neural Radiance Fields
- Authors:
- Jonathan T. Barron, Ben Mildenhall, Dor Verbin, Pratul P. Srinivasan, Peter Hedman
- Paper:
- Web:
- ID:
- zipnerf
Zip-NeRF is a radiance field method which addresses the aliasing problem in the case of hash-grid based methods (iNGP-based). Instead of sampling along the ray it samples along a spiral path - approximating integration along the frustum.