Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that generates a design representation to further construct a digital design multigraph and generate a structural representation for a digital design document from the digital design multigraph. For instance, the disclosed systems generate a design representation of a digital design document that includes design properties with multiple digital design elements. In particular, the disclosed systems construct a digital design (multi-)graph from the design representation by generating nodes to represent digital design elements and edges based on relationships between these elements. In addition, the disclosed systems generate a structural representation based on the digital design multigraph for downstream applications.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that generates a design representation to further construct a digital design multigraph and generate a structural representation for a digital design document from the digital design multigraph. For instance, the disclosed systems generate a design representation of a digital design document that includes design properties with multiple digital design elements. In particular, the disclosed systems construct a digital design (multi-)graph from the design representation by generating nodes to represent digital design elements and edges based on relationships between these elements. In addition, the disclosed systems generate a structural representation based on the digital design multigraph for downstream applications.

Abstract: Embodiments are disclosed for machine learning-based generation of recommended layouts. The method includes receiving a set of design elements for performing generative layout recommendation. A number of each type of design element from the set of design elements is determined. A set of recommended layouts are generated using a trained generative layout model and the number and type of design elements. The set of recommended layouts are output.

Abstract: The present disclosure is directed toward systems and methods for retargeting a user's input digital design based on a selected template digital design. For example, in response to the user's selection of a template digital design, one or more embodiments described herein change various design features of the user's input digital design to match corresponding design features in the selected template digital design. One or more embodiments described herein also provide template digital designs to the user for use in retargeting after a two-step selection process that ensures the provided template digital designs are compatible with the user's input digital design.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that generates a design representation to further construct a digital design multigraph and generate a structural representation for a digital design document from the digital design multigraph. For instance, the disclosed systems generate a design representation of a digital design document that includes design properties with multiple digital design elements. In particular, the disclosed systems construct a digital design (multi-) graph from the design representation by generating nodes to represent digital design elements and edges based on relationships between these elements. In addition, the disclosed systems generate a structural representation based on the digital design multigraph for downstream applications.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that generates a design representation to further construct a digital design multigraph and generate a structural representation for a digital design document from the digital design multigraph. For instance, the disclosed systems generate a design representation of a digital design document that includes design properties with multiple digital design elements. In particular, the disclosed systems construct a digital design (multi-) graph from the design representation by generating nodes to represent digital design elements and edges based on relationships between these elements. In addition, the disclosed systems generate a structural representation based on the digital design multigraph for downstream applications.

Abstract: Embodiments are disclosed for machine learning-based generation of recommended layouts. The method includes receiving a set of design elements for performing generative layout recommendation. A number of each type of design element from the set of design elements is determined. A set of recommended layouts are generated using a trained generative layout model and the number and type of design elements. The set of recommended layouts are output.

Abstract: The present disclosure is directed toward systems and methods for retargeting a user's input digital design based on a selected template digital design. For example, in response to the user's selection of a template digital design, one or more embodiments described herein change various design features of the user's input digital design to match corresponding design features in the selected template digital design. One or more embodiments described herein also provide template digital designs to the user for use in retargeting after a two-step selection process that ensures the provided template digital designs are compatible with the user's input digital design.

Abstract: The present disclosure is directed toward systems and methods for retargeting a user's input digital design based on a selected template digital design. For example, in response to the user's selection of a template digital design, one or more embodiments described herein change various design features of the user's input digital design to match corresponding design features in the selected template digital design. One or more embodiments described herein also provide template digital designs to the user for use in retargeting after a two-step selection process that ensures the provided template digital designs are compatible with the user's input digital design.

Abstract: The present disclosure is directed toward systems and methods for automatically generating combinations of styling values for application to a digital design. Each of the generated styling value combinations includes styling values selected from one or more probabilistically distributed sets of styling values. One or more embodiments described herein utilize a scoring system to ensure that, when applied to the digital design, the styling values included in the probabilistically distributed sets of styling values will make the digital design look professional and aesthetically pleasing.

Abstract: The present disclosure is directed toward systems and methods for determining the optimal placement, color, and size of an overlay in a digital design. For example, in response to determining that a change to an underlying image of a digital design has caused a loss of readability and/or aesthetic value in the digital design due to the placement of the overlay over the now changed underlying image, one or more embodiments described herein utilize a scoring system to identify optimal placement, color, and size for the overlay in relation to the underlying image in the digital design.

Abstract: The present disclosure is directed toward systems and methods for retargeting a user's input digital design based on a selected template digital design. For example, in response to the user's selection of a template digital design, one or more embodiments described herein change various design features of the user's input digital design to match corresponding design features in the selected template digital design. One or more embodiments described herein also provide template digital designs to the user for use in retargeting after a two-step selection process that ensures the provided template digital designs are compatible with the user's input digital design.

Abstract: The present disclosure is directed toward systems and methods for determining the optimal placement, color, and size of an overlay in a digital design. For example, in response to determining that a change to an underlying image of a digital design has caused a loss of readability and/or aesthetic value in the digital design due to the placement of the overlay over the now changed underlying image, one or more embodiments described herein utilize a scoring system to identify optimal placement, color, and size for the overlay in relation to the underlying image in the digital design.

Abstract: The present disclosure is directed toward systems and methods for automatically generating combinations of styling values for application to a digital design. Each of the generated styling value combinations includes styling values selected from one or more probabilistically distributed sets of styling values. One or more embodiments described herein utilize a scoring system to ensure that, when applied to the digital design, the styling values included in the probabilistically distributed sets of styling values will make the digital design look professional and aesthetically pleasing.