Original article was published by Mikhail Raevskiy on Artificial Intelligence on Medium
Researchers from MPI Informatik and University College London trained a neural network that changes the angle of view of a scene in an image. The neural network takes into account the change in lighting. To interpolate the viewing angle, time and lighting from a set of 2D images, which have coordinates marked, the neural network learns to draw each image from the others.
On inference, the model takes as input a set of coordinates that describe the parameters of the viewing angle, time and lighting. At the output, the model generates a 2D image in real time with the specified coordinates. At the same time, additional parameters can be added to the model, which will be taken into account when generating the image.