| CPC G06T 17/00 (2013.01) [G06T 7/50 (2017.01); G06T 7/75 (2017.01); G06T 19/20 (2013.01); G06V 40/171 (2022.01); G06T 2200/08 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30201 (2013.01); G06T 2219/2021 (2013.01)] | 30 Claims |

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1. A method of generating a three-dimensional (3D) facial model, the method comprising:
obtaining, by an image input of a machine learning model, at least one input image associated with a face;
generating, by the machine learning model based on the at least one input image associated with the face, a face feature vector, wherein the face feature vector encodes one or more features of the face;
obtaining, by a pose input of the machine learning model, a pose for a 3D facial model associated with the face;
generating, by the machine learning model based on the pose, a pose feature vector, wherein the pose feature vector encodes the pose, and wherein the pose is different from a pose of the face associated with the at least one input image;
combining the face feature vector and the pose feature vector to generate a combined feature vector; and
generating, by a neural network layer of the machine learning model based on the combined feature vector, the 3D facial model associated with the face, wherein one or more parameters associated with a shape component of the 3D facial model are conditioned on the pose.
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