Abstract: Using latent space manipulation and neural animation to generate hyperreal synthetic faces is described. A machine learning model(s) may be trained to generate a synthetic face of a subject featured in unaltered video content based at least in part on video data of an actor making a mouth-generated sound or a three-dimensional (3D) model of a face of the subject that has been animated in accordance with the mouth-generated sound. Latent space manipulation and neural animation may be used with the trained machine learning model(s) to generate instances of the synthetic face, and the instances of the synthetic face can be used to create altered video content featuring the subject with the synthetic face making the mouth-generated sound.

Abstract: Modifying source data to generate hyperreal synthetic content is described. Source data representing images of a body part of a subject may be modified to obtain training data, such as by modifying the body part in the images and/or by enhancing the images to improve the quality thereof. One or more machine learning models may be trained using the training data to obtain one or more trained machine learning models, and the trained model(s) is used to generate output data representing a synthetic body part based at least in part on input data representing an image featuring the body part of the subject, such as an image featuring the modified body part and/or an enhanced image featuring the body part. The output data is then used to generate media data corresponding to media content featuring the synthetic body part.

Abstract: Prompting a trained artificial intelligence (AI) model(s) to output photoreal synthetic content in real-time is described. In some examples, one or more AI models are trained using sequential video frames as training data to obtain one or more trained AI models configured to generate temporally-coherent output data. In an example process, user-provided prompt data representing a prompt provided by a user is received, output data representing synthetic content is generated using the trained AI model(s) based at least in part on the user-provided prompt data, and video content featuring the synthetic content is caused to be displayed on a display based at least in part on the output data. In some examples, the output data is provided to the trained AI model(s) as part of a feedback loop to generate further output data as part of a real-time, iterative prompting system.

Abstract: Using latent space manipulation and neural animation to generate hyperreal synthetic faces is described. A machine learning model(s) may be trained to generate a synthetic face of a subject featured in unaltered video content based at least in part on video data of an actor making a mouth-generated sound or a three-dimensional (3D) model of a face of the subject that has been animated in accordance with the mouth-generated sound. Latent space manipulation and neural animation may be used with the trained machine learning model(s) to generate instances of the synthetic face, and the instances of the synthetic face can be used to create altered video content featuring the subject with the synthetic face making the mouth-generated sound.