NeRFs
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Explore more → **NeRFs**
What is NeRFs?
NeRFs (Neural Radiance Fields) are a technique for representing 3D scenes using neural networks. They learn a continuous volumetric scene function that can be rendered from any viewpoint, enabling the creation of highly realistic and detailed 3D models from a set of 2D images. They are commonly used for novel view synthesis, 3D reconstruction, and virtual reality applications.
What other technologies are related to NeRFs?
NeRFs Competitor Technologies
GANs
Generative Adversarial Networks (GANs) are used for generating new images, and can be an alternative approach to generating novel views of a scene, thus a competitor to NeRFs.
diffusion models
Diffusion models, like GANs, can generate new images and are an alternative approach to generating novel views of a scene, and are therefore competitors to NeRFs.
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NeRFs Complementary Technologies
PyTorch
PyTorch is a deep learning framework often used to implement and train NeRF models. It provides the necessary tools for building and optimizing neural networks.
TensorFlow
TensorFlow is another deep learning framework that can be used to implement and train NeRF models. Like PyTorch, it provides tools for building and optimizing neural networks.
Number of organizations that mention technology
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Which job functions commonly mention NeRFs?
Applied Scientist
0.2% of all Applied Scientist jobs mention NeRFs
View 21
jobs on Sumble
Robotics Engineer
0.1% of all Robotics Engineer jobs mention NeRFs
View 4
jobs on Sumble
Machine Learning
45 Machine Learning jobs mention NeRFs
View 45
jobs on Sumble
Research Scientist
17 Research Scientist jobs mention NeRFs
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jobs on Sumble
AI Engineer
19 AI Engineer jobs mention NeRFs
View 19
jobs on Sumble
Which organizations are mentioning NeRFs?
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