Abstract: Systems and methods for eye tracking latency enhancements. An example head-mounted system obtains a first image of an eye of a user. The first image is provided as input to a machine learning model which has been trained to generate iris and pupil segmentation data given an image of an eye. A second image of the eye is obtained. A set of locations in the second image at which one or more glints are shown is detected based on iris segmentation data generated for the first image. A region of the second image at which the pupil of the eye of the user is shown is identified based on pupil segmentation data generated for the first image. A pose of the eye of the user is determined based on the detected set of glint locations in the second image and the identified region of the second image.

Abstract: Implementations of the subject technology provide visualizations of non-visible features of a physical environment, at the location of the non-visible features in the physical environment. The non-visible features may include wireless communications signals, sounds, airflow, gases, subsonic and/or ultrasonic waves, hidden objects, or the like. A device may store visual contexts for visualizations of particular non-visible features. The device may obtain a depth map that allows the device to determine the location of the non-visible feature in the physical environment and to overlay the visualization on a user's view of that location. In this way, the non-visible feature can be visualized its correct location, orientation, direction and/or strength in the physical environment.

Abstract: Implementations of the subject technology provide visualizations of non-visible features of a physical environment, at the location of the non-visible features in the physical environment. The non-visible features may include wireless communications signals, sounds, airflow, gases, subsonic and/or ultrasonic waves, hidden objects, or the like. A device may store visual contexts for visualizations of particular non-visible features. The device may obtain a depth map that allows the device to determine the location of the non-visible feature in the physical environment and to overlay the visualization on a user's view of that location. In this way, the non-visible feature can be visualized its correct location, orientation, direction and/or strength in the physical environment.

Abstract: Implementations of the subject technology provide visualizations of non-visible features of a physical environment, at the location of the non-visible features in the physical environment. The non-visible features may include wireless communications signals, sounds, airflow, gases, subsonic and/or ultrasonic waves, hidden objects, or the like. A device may store visual contexts for visualizations of particular non-visible features. The device may obtain a depth map that allows the device to determine the location of the non-visible feature in the physical environment and to overlay the visualization on a user's view of that location. In this way, the non-visible feature can be visualized its correct location, orientation, direction and/or strength in the physical environment.

Abstract: Systems and methods for eye tracking latency enhancements. An example head-mounted system obtains a first image of an eye of a user. The first image is provided as input to a machine learning model which has been trained to generate iris and pupil segmentation data given an image of an eye. A second image of the eye is obtained. A set of locations in the second image at which one or more glints are shown is detected based on iris segmentation data generated for the first image. A region of the second image at which the pupil of the eye of the user is shown is identified based on pupil segmentation data generated for the first image. A pose of the eye of the user is determined based on the detected set of glint locations in the second image and the identified region of the second image.

Abstract: Implementations of the subject technology provide visualizations of non-visible features of a physical environment, at the location of the non-visible features in the physical environment. The non-visible features may include wireless communications signals, sounds, airflow, gases, subsonic and/or ultrasonic waves, hidden objects, or the like. A device may store visual contexts for visualizations of particular non-visible features. The device may obtain a depth map that allows the device to determine the location of the non-visible feature in the physical environment and to overlay the visualization on a user's view of that location. In this way, the non-visible feature can be visualized its correct location, orientation, direction and/or strength in the physical environment.

Abstract: Implementations of the subject technology provide visualizations of non-visible features of a physical environment, at the location of the non-visible features in the physical environment. The non-visible features may include wireless communications signals, sounds, airflow, gases, subsonic and/or ultrasonic waves, hidden objects, or the like. A device may store visual contexts for visualizations of particular non-visible features. The device may obtain a depth map that allows the device to determine the location of the non-visible feature in the physical environment and to overlay the visualization on a user's view of that location. In this way, the non-visible feature can be visualized its correct location, orientation, direction and/or strength in the physical environment.

Abstract: Implementations of the subject technology provide visualizations of non-visible features of a physical environment, at the location of the non-visible features in the physical environment. The non-visible features may include wireless communications signals, sounds, airflow, gases, subsonic and/or ultrasonic waves, hidden objects, or the like. A device may store visual contexts for visualizations of particular non-visible features. The device may obtain a depth map that allows the device to determine the location of the non-visible feature in the physical environment and to overlay the visualization on a user's view of that location. In this way, the non-visible feature can be visualized its correct location, orientation, direction and/or strength in the physical environment.