System and method for generating training data from synthetic images

Abstract

In one embodiment, example systems and methods relate to a manner of generating training data for a classifier or a regression function using labeled synthetic images and a mapping that accounts for the differences between synthetic images and real images. The mapping may be a neural network that was trained using image pairs that each include an image of an object and a synthetic image that is generated from the image of the object by overlaying a rendering of the object into the image. The mapping may recognize the differences between features of the object in the real image and features of the rendering of the object in the synthetic image such as color, contrast, sensor noise, etc. Later, a set of labeled synthetic images is received, and the mapping is used to generate training data from the labeled synthetic images.