Systems and methods for layered image generation

A computer implemented method for generating a multi-layer image based on text input, the method comprising:

• generating, using a trained machine learning model and based on the text input, a single-layer image comprising a plurality of objects;
• segmenting the single-layer image to generate a plurality of images, each image of the plurality of images comprising a depiction of a respective object of the plurality of objects of the single-layer image;
• determining that, as a result of the segmenting, each respective image of the plurality of images comprises one or more empty regions at a portion of the respective image at which one or more objects of the plurality of objects is depicted in the single-layer image;
• determining that a size of at least one empty region of the one or more empty regions does not exceed a threshold;
• in response to determining that the size of the at least one empty region does not exceed the threshold, modifying the at least one empty region of the one or more empty regions by causing the at least one empty region to be filled in;
• extracting, from the text input, a portion of the text input describing a background portion of the single-layer image;
• generating, using the trained machine learning model and based on the extracted portion of the text input, a background image;
• and
• generating the multi-layer image based on the plurality of images and the background image, wherein generating the multi-layer image is based on the plurality of images, having the at least one modified empty region, and the background image.

A computer-implemented system for generating a multi-layer image based on text input, the system comprising:

• control circuitry configured to:
• generate, using a trained machine learning model and based on the text input, a single-layer image comprising a plurality of objects;
• segment the single-layer image to generate a plurality of images, each image of the plurality of images comprising a depiction of a respective object of the plurality of objects of the single-layer image;
• determine that, as a result of the segmenting, each respective image of the plurality of images comprises one or more empty regions at a portion of the respective image at which one or more objects of the plurality of objects is depicted in the single-layer image;
• determine that a size of at least one empty region of the one or more empty regions does not exceed a threshold;
• in response to determining that the size of the at least one empty region does not exceed the threshold, modify the at least one empty region of the one or more empty regions by causing the at least one empty region to be filled in;
• extract, from the text input, a portion of the text input describing a background portion of the single-layer image;
• generate, using the trained machine learning model and based on the extracted portion of the text input, a background image;
• and
• generate the multi-layer image based on the plurality of images and the background image, wherein generating the multi-layer image is based on the plurality of images, having the at least one modified empty region, and the background image.