up:: π€ Artificial Intelligence
type:: #π
status:: #π/π±
tags:: #on/ai
topics:: Technology
links::
NeRFs
NeRFs (Neural Radiance Fields) are a deep learning architecture that model the 3D geometry and appearance of a scene from a collection of 2D images, allowing for high-quality rendering and novel view synthesis.
NeRF (Neural Radiance Fields) is a type of machine learning algorithm used in computer graphics to generate photorealistic 3D models from 2D images. It uses deep neural networks to learn the geometry, appearance, and lighting conditions of a scene from several photographs of the same object or environment taken from different angles. NeRFs are capable of creating high-fidelity renderings with accurate lighting and reflections, resulting in realistic 3D representations that can be used in virtual reality, video games, and other applications.What are NeRFs?
NeRF, or neural radiance field AI (artificial intelligence) models, are changing theΒ 3DΒ game.
NeRF models can generate a 3D scene from a sparse collection of 2D images of that scene. At the core of NeRF models core sits a neural network that can fill in the gaps and correct for human error.Β This process is often called volume rendering or reverse rendering because it reconstructs the original 3D scene from which 2D images were rendered or captured.