Neural Radiance Fields (NeRF)

5 Posts

Illustration of the multiresolution hash encoding in 2D
Neural Radiance Fields (NeRF)

Novel Views of 3D Scenes — Pronto: Using NeRF Algorithms to Quickly Generate New 3D Views

Given a number of images of the same scene, a neural network can synthesize images from novel vantage points, but it can take hours to train. A new approach cuts training time to a few minutes.
Series of images showing how single trained network generates 3D reconstructions of multiple scenes
Neural Radiance Fields (NeRF)

One Network, Many Scenes

To reconstruct the 3D world behind a set of 2D images, machine learning systems usually require a dedicated neural network for each scene. New research enables a single trained network to generate 3D reconstructions of multiple scenes.
Neural networks generating novel views of a 3D scene based on existing pictures
Neural Radiance Fields (NeRF)

3D Scene Synthesis for the Real World

Researchers have used neural networks to generate novel views of a 3D scene based on existing pictures plus the positions and angles of the cameras that took them. In practice, though, you may not know the precise camera
FastNeRF accelerates the photorealistic 3D rendering method
Neural Radiance Fields (NeRF)

Virtual Reality in Real Time

Ideally, real-time 3D applications such as virtual and augmented reality transition smoothly between different viewpoints of a scene — but generating a fresh perspective can take time. New research speeds the process.
Neural Body, a procedure that generates novel views of a single human character, working
Neural Radiance Fields (NeRF)

Seeing People From a New Angle

The University of Hong Kong, and Cornell University to create Neural Body, a procedure that generates novel views of a single human character based on shots from only a few angles.

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