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NeRF

NeRF

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What is NeRF?

NeRF (Neural Radiance Field) is a technique that uses neural networks to represent complex 3D scenes from a set of 2D images. It learns a continuous volumetric scene function that can be rendered from novel viewpoints. Commonly used for photorealistic view synthesis, novel view generation, and 3D reconstruction.

What other technologies are related to NeRF?

NeRF Competitor Technologies

Gaussian Splatting is an alternative method for novel view synthesis that offers real-time rendering and fast training compared to NeRF.
mentioned alongside NeRF in 52% (135) of relevant job posts

NeRF Complementary Technologies

3D reconstruction techniques are used to create the 3D scene representations that NeRFs can then use for novel view synthesis. Can also be used to generate training data for NeRF.
mentioned alongside NeRF in 7% (55) of relevant job posts
Diffusion models can be used to improve NeRF training by generating high-quality training data or by regularizing the NeRF model.
mentioned alongside NeRF in 3% (56) of relevant job posts
PyTorch is a deep learning framework commonly used to implement and train NeRF models.
mentioned alongside NeRF in 0% (236) of relevant job posts

Which organizations are mentioning NeRF?

Organization
Industry
Matching Teams
Matching People
NeRF
Apple
Scientific and Technical Services
NeRF
NVIDIA
Scientific and Technical Services
NeRF
Microsoft
Scientific and Technical Services

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