Face swapping with neural network-based geometry refining

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

• receiving a first image including a face associated with a first facial identity;
• generating, via a machine learning model, at least a first texture map and a first position map based on the first image, wherein the machine learning model comprises a plurality of decoders, wherein each decoder included in the plurality of decoders is trained on images corresponding to a different facial identity;
• and
• rendering a second image including a face associated with a second facial identity based on the first texture map and the first position map, wherein the second facial identity is different from the first facial identity.

A computer system comprising:

• one or more processors;
• and
• one or more memories storing instructions that, when executed by the one or more processors, cause the one or more processors to:
• receive a first image including a face associated with a first facial identity;
• generate, via a machine learning model, at least a first texture map and a first position map based on the first image, wherein the machine learning model comprises a plurality of decoders, wherein each decoder included in the plurality of decoders is trained on images corresponding to a different facial identity;
• and
• render a second image including a face associated with a second facial identity based on the first texture map and the first position map, wherein the second facial identity is different from the first facial identity.