[Paper] Compressing Light Field as Multiplane Image

Abstract

A light field contains a large amount of data because it is represented as a dense set of multi-view images. We propose a method of compressing a light field as a newly emerging representation called a multiplane image (MPI), a graphics-oriented representation composed of a stack of semi-transparent images. Our method was constructed on a deep convolutional neural network (CNN), which was trained to generate an MPI from the given light field. To draw out the potential of this representation, we trained the CNN to be overfitted to the target light field. We also encouraged spatial smoothness to make the MPI easier to compress. Despite being in the early stage of development, our method has already achieved promising rate-distortion performance.