1. A computer-implemented method, comprising: accessing, by a computer system, data identifying a set of first seed images, each first seed image being classified as belonging to a first category of images based on signal data of the first seed image that are independent of image content of the first seed image, and wherein the set of first seed images is a proper subset of images in an image corpus; for each first seed image: determining, by the computer system, a respective first set of similar images from images in the image corpus, each similar image in the respective first set of images having a visual similarity score that is a measure of visual similarity of the similar image to the first seed image based on the image content of the similar image and the first seed image, and that satisfies a first seed image similarity threshold; and for each similar image in each respective first set of similar images: attributing, by the computer system, to the similar image the signal data of each first seed image for which the similar image has a respective visual similarity score satisfying the first seed image similarity threshold; determining, by the computer system, whether the similar image belongs to the first category of images based on the image signal data attributed to the similar image; and classifying, by the computer system, only the similar images that are determined to belong the first category as belonging to the first category of images; wherein the first category of images are images that have been classified as spoof images.