Generating styles for neural style transfer in three-dimensional shapes

One or more non-transitory computer-readable media storing instructions that, when executed by one or more processors, cause the one or more processors to perform the steps of:

• determining a distribution associated with a plurality of style codes for a plurality of three-dimensional (3D) shapes, wherein each style code included in the plurality of style codes represents a difference between a first 3D shape and a second 3D shape, and wherein the second 3D shape is generated by applying one or more augmentations to the first 3D shape;
• sampling from the distribution to generate an additional style code;
• executing a first trained machine learning model based on the additional style code to generate an output 3D shape having one or more style-based attributes associated with the additional style code and one or more content-based attributes associated with an object;
• and
• generating a 3D model of the object based on the output 3D shape.

A system, comprising:

• one or more memories that store instructions, and
• one or more processors that are coupled to the one or more memories and,
• when executing the instructions, are configured to perform the steps of:
• determining a distribution associated with a plurality of style codes for a plurality of three-dimensional (3D) shapes, wherein each style code included in the plurality of style codes represents a difference between a first 3D shape and a second 3D shape, and wherein the second 3D shape is generated by applying one or more augmentations to the first 3D shape;
• sampling from the distribution to generate an additional style code;
• executing a first trained machine learning model based on the additional style code to generate an output 3D shape having one or more style-based attributes associated with the additional style code and one or more content-based attributes associated with an object;
• and
• generating a 3D model of the object based on the output 3D shape.