Google patents method to keep objects consistent in AI-generated images

1. A computing system for image generation, the system comprising: one or more processors; and one or more non-transitory computer-readable media that collectively store instructions that, when executed by the one or more processors, cause the computing system to perform operations, the operations comprising: obtaining input data, wherein the input data comprises one or more input images, wherein the one or more input images are descriptive of a particular object; processing the input data with an image generation model to generate output data, wherein the image generation model has been trained to generate a set of model-generated images based on an input, wherein the output data comprises a plurality of output model-generated images, wherein the plurality of output model-generated images are descriptive of the particular object in one or more environments, wherein processing input data with the image generation model to generate the output data comprises: tuning a set of parameters of the image generation model based on the one or more input images; embedding an association between a model-readable token and the set of parameters within the image generation model; generating a plurality of prompts that comprise the model-readable token; and generating, by processing the plurality of prompts with the image generation model, the plurality of output model-generated images based at least in part on the set of parameters tuned based on the one or more input images, wherein the set of parameters render the particular object based on the image generation model processing the model-readable token; and providing at least a subset of the plurality of output model-generated images as output.