Apparatus and methods for image reconstruction using machine learning processes

A method comprising:

• applying a first trained machine learning process to an image and generate coefficient data characterizing the image in a plurality of dimensions based on the application of the first trained machine learning process to the image;
• generating first mesh data characterizing a first mesh of the image based on the coefficient data;
• applying a second trained machine learning process to the coefficient data and the image and generate displacement data characterizing a displacement image based on the application of the second trained machine learning process to the coefficient data and the image;
• and
• generating second mesh data characterizing a second mesh of the image based on a combination of at least one vertex of the first mesh data and at least one vertex of the displacement data corresponding to a same coordinate.

A non-transitory, machine-readable storage medium storing instructions that, when executed by at least one processor, causes the at least one processor to perform operations that include:

• applying a first trained machine learning process to an image and generate coefficient data characterizing the image in a plurality of dimensions based on the application of the first trained machine learning process to the image;
• generating first mesh data characterizing a first mesh of the image based on the coefficient data;
• applying a second trained machine learning process to the coefficient data and the image and generate displacement data characterizing a displacement image based on the application of the second trained machine learning process to the coefficient data and the image;
• and
• generating second mesh data characterizing a second mesh of the image based on a combination of at least one vertex of the first mesh data and at least one vertex of the displacement data corresponding to a same coordinate.