NeRF
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Explore more → **NeRF**
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
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NeRF Complementary Technologies
3D reconstruction
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.
diffusion models
Diffusion models can be used to improve NeRF training by generating high-quality training data or by regularizing the NeRF model.
PyTorch
PyTorch is a deep learning framework commonly used to implement and train NeRF models.
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Which job functions commonly mention NeRF?
Research Scientist
0.1% of all Research Scientist jobs mention NeRF
View 62
jobs on Sumble
Machine Learning
0.1% of all Machine Learning jobs mention NeRF
View 117
jobs on Sumble
AI Engineer
0.1% of all AI Engineer jobs mention NeRF
View 49
jobs on Sumble
Researcher
104 Researcher jobs mention NeRF
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jobs on Sumble
Data, Analytics & Machine Learning
189 Data, Analytics & Machine Learning jobs mention NeRF
View 189
jobs on Sumble
Which organizations are mentioning NeRF?
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