ESTIMATING 3D SCENE REPRESENTATIONS OF IMAGES

Methods and systems are disclosed for performing operations for estimating a 3D scene representation from one or multiple 2D images. The operations include: receiving one or multiple two-dimensional (2D) images representing a real-world environment; and generating, by a machine learning model, a three-dimensional (3D) scene representation of the 2D image, which explicitly (separately) defines the a 3D shape and appearance of the background as well as a 3D position, 3D shape and appearance of each object of the scene depicted in the set of images, where the machine learning model has been trained in an unsupervised approach from a dataset of images and their camera poses (e.g. without any manually labelled annotations, such as depth maps, segmentation masks, object poses).