New technique improves AI ability to map 3D space with 2D cameras
Researchers have developed a technique that allows artificial intelligence (AI) programs to better map three-dimensional spaces using two-dimensional images captured by multiple cameras. Because the technique works effectively with limited computational resources, it holds promise for improving the navigation of autonomous vehicles.
Researchers have developed a technique that allows artificial intelligence (AI) programs to better map three-dimensional spaces using two-dimensional images captured by multiple cameras. Because the technique works effectively with limited computational resources, it holds promise for improving the navigation of autonomous vehicles.
Photos are two-dimensional (2D), but autonomous vehicles and other technologies have to navigate the three-dimensional (3D) world. Researchers have developed a new method to help artificial intelligence (AI) extract 3D information from 2D images, making cameras more useful tools for these emerging technologies.
Neural Radiance Fields (NeRF) is a fascinating technique that creates three-dimensional (3D) representations of a scene from a set of two-dimensional (2D) images, captured from different angles. It works by training a deep neural network to predict the color and density at any point in 3D space.