Multi-attribute inversion for text-to-image synthesis

A method for training a machine learning model, comprising:

• obtaining training data including a first attribute token representing a first attribute, and a second attribute token representing a second attribute;
• identifying a first set of layers of an image generation model and a first set of time-steps for the first attribute token and a second set of layers of the image generation model and a second set of time-steps for the second attribute token;
• and
• training the image generation model to generate synthetic images comprising the first attribute and the second attribute by providing the first attribute token to the first set layers of the image generation model during the first set of time-steps and providing the second attribute token to the second set of layers of the image generation model during the second set of time-steps.

Apparatus for image processing, comprising:

• at least one processor;
• at least one memory storing instruction executable by the at least one processor;
• and
• the apparatus further comprising an image generation model comprising parameters stored in the at least one memory and trained to generate synthetic images comprising a first attribute and a second attribute by providing a first attribute token to a first set layers of the image generation model during a first set of time-steps and providing a second attribute token to a second set of layers of the image generation model during a second set of time-steps.