Systems for determining image masks using multiple input images

Abstract

To identify sets of pixels in a first image that correspond to different objects or a background, a first image is provided to a Generative Adversarial Network (GAN). The GAN determines alternate images that retain the structural characteristics of the first image, such as the locations and shapes of objects, while modifying style characteristics, such as the colors of pixels. The images generated by the GAN may then be analyzed, such as by using a k-means clustering algorithm, to determine sets of pixels at the same location that change color in a similar manner across the set of images. A set of pixels that changes in a similar manner across the images generated by the GAN may be used as a mask representing an object or background to enable modification of the image without interfering with other objects.