Abstract: Implementations generally relate to providing augmented reality in a web browser. In one implementation, a method includes capturing images of a physical scene with a camera of a device. The method further includes determining motion of the camera using six degrees of freedom (6DoF) markerless tracking. The method further includes overlaying virtual three-dimensional (3D) content onto a depicted physical scene in the images, resulting in augmented reality (AR) images. The method further includes rendering the AR images in a browser of the device.

Abstract: Implementations generally relate to metaverse content modality mapping. In some implementations, a method includes obtaining functionality developed for a first modality of a virtual environment. The method further includes mapping the functionality to a second modality of the virtual environment. The method further includes executing the functionality developed for the first modality based on user interaction associated with the second modality.

Abstract: Implementations generally relate to providing augmented reality in a web browser. In one implementation, a method includes capturing images of a physical scene with a camera of a device. The method further includes determining motion of the camera using six degrees of freedom (6DoF) markerless tracking. The method further includes overlaying virtual three-dimensional (3D) content onto a depicted physical scene in the images, resulting in augmented reality (AR) images. The method further includes rendering the AR images in a browser of the device.

Abstract: Implementations generally relate to determining camera motion. In one implementation, a method includes capturing a first image and a second image of a physical scene with a camera in respective first and second positions. The method further includes determining first and second image points from the respective first and second image points. The method further includes determining first and second directions of gravity relative to the camera in the respective first and second positions. The method further includes determining a motion of the camera between the capturing of the first image and the capturing of the second image, wherein the determining of the motion of the camera is based at least in part on the first image points, the second image points, the first direction of gravity, and the second direction of gravity.

Abstract: Implementations generally relate to providing augmented reality in a web browser. In one implementation, a method includes capturing images of a physical scene with a camera of a device. The method further includes determining motion of the camera using six degrees of freedom (6DoF) marker-based tracking. The method further includes determining positions of markers relative to the camera using 6DoF marker-based tracking. The method further includes overlaying virtual content onto a depicted physical scene in the images, resulting in augmented reality (AR) images. The method further includes rendering the AR images in a browser of the device.

Abstract: Implementations generally relate to providing augmented reality in a web browser. In one implementation, a method includes capturing images of a physical scene with a camera of a device. The method further includes determining motion of the camera using six degrees of freedom (6DoF) marker-based tracking. The method further includes determining positions of markers relative to the camera using 6DoF marker-based tracking. The method further includes overlaying virtual content onto a depicted physical scene in the images, resulting in augmented reality (AR) images. The method further includes rendering the AR images in a browser of the device.

Abstract: Implementations generally relate to determining camera motion. In one implementation, a method includes capturing a first image and a second image of a physical scene with a camera in respective first and second positions. The method further includes determining first and second image points from the respective first and second image points. The method further includes determining first and second directions of gravity relative to the camera in the respective first and second positions. The method further includes determining a motion of the camera between the capturing of the first image and the capturing of the second image, wherein the determining of the motion of the camera is based at least in part on the first image points, the second image points, the first direction of gravity, and the second direction of gravity.

Abstract: Implementations generally relate to providing augmented reality in a web browser. In one implementation, a method includes capturing images of a physical scene with a camera of a device. The method further includes determining motion of the camera using six degrees of freedom (6DoF) markerless tracking. The method further includes overlaying virtual three-dimensional (3D) content onto a depicted physical scene in the images, resulting in augmented reality (AR) images. The method further includes rendering the AR images in a browser of the device.

Abstract: Implementations generally relate to localizing and mapping. In one implementation, a method includes determining one or more map points in a point cloud space, where the point cloud space corresponds to a real physical environment. The method further includes determining movement information of one or more of the map points, where the determining of the movement information is performed by a neural network. The method further includes determining a self-position in the point cloud space based on the determined movement information.

Abstract: Various embodiments for event-based information sharing are disclosed. In one example embodiment, an event definition describing an event is determined. An event geofence associated with a location of the event is generated and content is shared between invitees attending the event and located within an area of the event geofence.

Abstract: Implementations generally relate to localizing and mapping. In one implementation, a method includes determining one or more map points in a point cloud space, where the point cloud space corresponds to a real physical environment. The method further includes determining movement information of one or more of the map points, where the determining of the movement information is performed by a neural network. The method further includes determining a self-position in the point cloud space based on the determined movement information.

Abstract: Implementations generally relate to generating compositional media content. In some implementations, a method includes receiving a plurality of photos from a user, and determining one or more composition types from the photos. The method also includes generating compositions from the selected photos based on the one or more determined composition types. The method also includes providing the one or more generated compositions to the user.

Abstract: Implementations relate to detecting spherical images. In some implementations, a computer-executed method includes obtaining an image, examining at least one characteristic of the image, and determining that the image is a spherical image based on the at least one examined characteristic. The method modifies metadata associated with the image to designate the image for spherical display.

Abstract: Implementations relate to providing selected images from a set of images. In some implementations, a computer-executed method includes receiving a request from a device for one or more images, where the request specifies one or more specified time periods at each of one or more specified time scales. One or more groups of selected images are determined from a set of images, each group being within one of the one or more specified time periods at one of the one or more specified time scales. One or more of the selected images from the one or more groups are caused to be sent to the device.

Abstract: In some implementations, a method provides image candidates for a user. The method can include applying a plurality of different image adjustment types to an image to produce a plurality of different adjusted images. A score is determined for each of the adjusted images, where each score is based on previous selections by a plurality of persons of other images having one or more characteristics similar to the adjusted images. The method determines one or more candidate images for presentation to a particular user, where each candidate image is obtained from one of the different image adjustment types. The candidate images are determined based on the scores of the adjustment types.

Abstract: Implementations generally relate to generating photo animations. In some implementations, a method includes receives a plurality of photos from a user. The method also includes selecting photos from the plurality of photos that meet one or more predetermined similarity criteria. The method also includes generating an animation using the selected photos.

Abstract: In some implementations, a method rotates images based on image content to correct image orientation. In some implementations, a method includes obtaining one or more identifications of content depicted in an image and determining a current orientation of the content depicted in the image. The current orientation is determined based on the one or more identifications of the content. An amount of rotation for the image is determined that orients the content closer to a predetermined reference orientation than to the current orientation. The image is rotated by the determined amount.

Abstract: Implementations generally relate to generating compositional media content. In some implementations, a method includes receiving a plurality of photos from a user, and determining one or more composition types from the photos. The method also includes generating compositions from the selected photos based on the one or more determined composition types. The method also includes providing the one or more generated compositions to the user.

Abstract: In some implementations, a method provides color corrections based on multiple images. In some implementations, a method includes determining one or more characteristics of each of a plurality of source images and determining one or more similarities between the one or more characteristics of different source images. The source images are grouped into one or more groups of one or more target images based on the determined similarities. The method determines and applies one or more color corrections to the one or more target images in at least one of the groups.

Abstract: In some implementations, a method provides color corrections based on multiple images. In some implementations, a method includes determining one or more characteristics of each of a plurality of source images and determining one or more similarities between the one or more characteristics of different source images. The source images are grouped into one or more groups of one or more target images based on the determined similarities. The method determines and applies one or more color corrections to the one or more target images in at least one of the groups.