Tetra-NeRF: Representing Neural Radiance Fields Using Tetrahedra
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F23%3A00369657" target="_blank" >RIV/68407700:21230/23:00369657 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21730/23:00369657
Result on the web
<a href="https://doi.org/10.1109/ICCV51070.2023.01692" target="_blank" >https://doi.org/10.1109/ICCV51070.2023.01692</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICCV51070.2023.01692" target="_blank" >10.1109/ICCV51070.2023.01692</a>
Alternative languages
Result language
angličtina
Original language name
Tetra-NeRF: Representing Neural Radiance Fields Using Tetrahedra
Original language description
Neural Radiance Fields (NeRFs) are a very recent and very popular approach for the problems of novel view syn thesis and 3D reconstruction. A popular scene representa tion used by NeRFs is to combine a uniform, voxel-based subdivision of the scene with an MLP. Based on the ob servation that a (sparse) point cloud of the scene is often available, this paper proposes to use an adaptive represen tation based on tetrahedra obtained by Delaunay triangula tion instead of uniform subdivision or point-based represen tations. We show that such a representation enables efficient training and leads to state-of-the-art results. Our approach elegantly combines concepts from 3D geometry process ing, triangle-based rendering, and modern neural radiance fields. Compared to voxel-based representations, ours pro vides more detail around parts of the scene likely to be close to the surface. Compared to point-based representations, our approach achieves better performance. The source code is publicly available at: https://jkulhanek.com/tetra-nerf.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GX23-07973X" target="_blank" >GX23-07973X: A Unified 3D Map Representation</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
ICCV2023: Proceedings of the International Conference on Computer Vision
ISBN
979-8-3503-0719-1
ISSN
1550-5499
e-ISSN
2380-7504
Number of pages
12
Pages from-to
18412-18423
Publisher name
IEEE
Place of publication
Piscataway
Event location
Paris
Event date
Oct 2, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001169500503004