Facial expression and pose transfer utilizing an end-to-end machine learning model

This invention describes a computer method for changing a person's facial expression and body pose in a digital image. It works by analyzing a target image to extract the desired expression and pose, and then applying those features to a person in a different source image. The core of the system relies on a specialized 3D encoder and a generative neural network to achieve this transformation.

Why it matters: Filed as generative AI was rapidly evolving. The performance and fidelity of 3D encoders and generative neural networks for image manipulation have significantly advanced since 2023, making robust implementation more practical.

Status: Under examinationA pending application. It has not been granted, and it has not been abandoned.
How hard to build: SpecializedHeavy software system, machine learning models

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