Abstract: Various implementations disclosed herein include devices, systems, and methods that generates values for a representation of a face of a user. For example, an example process may include obtaining sensor data (e.g., live data) of a user, wherein the sensor data is associated with a point in time, generating a set of values representing the user based on the sensor data, and providing the set of values, where a depiction of the user at the point in time is displayed based on the set of values. In some implementations, the set of values includes depth values that define three-dimensional (3D) positions of portions of the user relative to multiple 3D positions of points of a projected surface and appearance values (e.g., color, texture, opacity, etc.) that define appearances of the portions of the user.

Abstract: Sensor data indicating a user's response to an avatar experience in which the user experiences a rendered avatar model is obtained. A perceptual quality metric value corresponding to the rendered avatar model is determined based on the sensor data and a determined relationship between the sensor data and the perceptual quality metric value. The avatar model is re-rendered for display based on the perceptual quality metric value.

Abstract: Rendering an avatar in a selected environment may include determining as inputs into an inferred shading network, an expression geometry to be represented by an avatar, head pose, and camera angle, along with a lighting representation for the selected environment. The inferred shading network may then generate a texture of a face to be utilized in rendering the avatar. The lighting representation may be obtained as lighting latent variables which are obtained from an environment autoencoder trained on environment images with various lighting conditions.

Abstract: Rendering an avatar in a selected environment may include determining as inputs into an inferred shading network, an expression geometry to be represented by an avatar, head pose, and camera angle, along with a lighting representation for the selected environment. The inferred shading network may then generate a texture of a face to be utilized in rendering the avatar. The lighting representation may be obtained as lighting latent variables which are obtained from an environment autoencoder trained on environment images with various lighting conditions.

Abstract: Various implementations disclosed herein include devices, systems, and methods that generates values for a representation of a face of a user. For example, an example process may include obtaining sensor data (e.g., live data) of a user, wherein the sensor data is associated with a point in time, generating a set of values representing the user based on the sensor data, and providing the set of values, where a depiction of the user at the point in time is displayed based on the set of values. In some implementations, the set of values includes depth values that define three-dimensional (3D) positions of portions of the user relative to multiple 3D positions of points of a projected surface and appearance values (e.g., color, texture, opacity, etc.) that define appearances of the portions of the user.

Abstract: Various implementations disclosed herein include devices, systems, and methods that generates and displays a portion of a representation of a face of a user. For example, an example process may include obtaining a first set of data corresponding to features of a face of a user in a plurality of configurations, while a user is using an electronic device, obtaining a second set of data corresponding to one or more partial views of the face from one or more image sensors, generating a representation of the face of the user based on the first set of data and the second set of data, wherein portions of the representation correspond to different confidence values, and displaying the portions of the representation based on the corresponding confidence values.

Abstract: Rendering an avatar in a selected environment may include determining as inputs into an inferred shading network, an expression geometry to be represented by an avatar, head pose, and camera angle, along with a lighting representation for the selected environment. The inferred shading network may then generate a texture of a face to be utilized in rendering the avatar. The lighting representation may be obtained as lighting latent variables which are obtained from an environment autoencoder trained on environment images with various lighting conditions.