Abstract: In some implementations, a computing device may create a semantic mapping that includes identified features that appear in a particular percentage of assets in a subset of assets of a media library. Also, the computing device may analyze assets of the media library using the semantic mapping to generate semantic scores, which may be used to determine a first tier of assets from the media library that rate highest for semantic score out of all assets. The computing device may present at least one of the first tier assets prominently in a user interface when viewing assets of the media library.

Abstract: The present disclosure generally relates to generating a video corresponding to a memory (e.g., an event or context) from media assets on a device. In some embodiments, the device receives user inputs requesting a video based on a natural language description of a memory. The device sends information of the natural language description to a first machine-learning (ML) model, and receives query tokens, which are used to find media items on the device that match the query tokens. The device sends information representing the found media items to another ML model that determines traits from the media items. These traits are sent to a third ML model to generate a story outline, and the video is generated by comparing the descriptions of shots in the story outline to visual embeddings of the found media assets to curate and arrange them into the video consistent with the story outline.

Abstract: The present disclosure generally relates to navigation, display, and/or presentation of content.

Abstract: Devices, methods, and non-transitory program storage devices (NPSDs) are disclosed herein to provide for the privacy-respectful learning of iconic scenes and places, wherein the learning is based on information received from one or more client devices in response to one or more collection criteria specified as part of one or more collection operations launched by a server device. In some embodiments, differential privacy techniques (such as the submission of predetermined amounts of noise-injecting, e.g., randomly-generated, data in conjunction with actual data) are employed by the client devices, such that any insights learned by the server device only relate to “hot spots,” “themes,” or other scenes, objects, and/or topics that are highly popular and captured in the digital assets (DAs) of many users, ensuring there is no way for the server device to learn or glean any insights related to particular users of individual client devices participating in the collection operations.

Abstract: Techniques for suggesting media assets, the technique including: requesting a set of candidate media assets for a set of user media items based on a knowledge graph metadata network describing the set of user media items; receiving metadata for the set of candidate media assets; determining one or more sets of ranked media assets based on the received metadata; and outputting the determined one or more sets of ranked media assets.

Abstract: In some implementations, a computing device may create a semantic mapping that includes identified features that appear in a particular percentage of assets in a subset of assets of a media library. Also, the computing device may analyze assets of the media library using the semantic mapping to generate semantic scores, which may be used to determine a first tier of assets from the media library that rate highest for semantic score out of all assets. The computing device may present at least one of the first tier assets prominently in a user interface when viewing assets of the media library.

Abstract: The present disclosure generally relates to retrieving and displaying contextually-relevant media content. In some embodiments, a device receives a request to display contextually-relevant media and, in response, displays a representation of a collection of media items relevant to a context of the device. In some embodiments, a device displays a visual media item of a sequence of items and, in response to receiving a swipe gesture, displays a detail user interface comprising related content for the media item. In some embodiments, a device, while displaying a first detail user interface, displays an affordance corresponding to a plurality of individuals identified as having attended a first event, that when selected, causes display of visual media corresponding to a plurality of events attended by the individuals. In some embodiments, a device, in response to user input, obtains an automatically-generated collection of visual media and displays a corresponding affordance.

Abstract: In some implementations, a computing device may create a semantic mapping that includes identified features that appear in a particular percentage of assets in a subset of assets of a media library. Also, the computing device may analyze assets of the media library using the semantic mapping to generate semantic scores, which may be used to determine a first tier of assets from the media library that rate highest for semantic score out of all assets. The computing device may present at least one of the first tier assets prominently in a user interface when viewing assets of the media library.

Abstract: The present disclosure generally relates to retrieving and displaying contextually-relevant media content. In some embodiments, a device receives a request to display contextually-relevant media and, in response, displays a representation of a collection of media items relevant to a context of the device. In some embodiments, a device displays a visual media item of a sequence of items and, in response to receiving a swipe gesture, displays a detail user interface comprising related content for the media item. In some embodiments, a device, while displaying a first detail user interface, displays an affordance corresponding to a plurality of individuals identified as having attended a first event, that when selected, causes display of visual media corresponding to a plurality of events attended by the individuals. In some embodiments, a device, in response to user input, obtains an automatically-generated collection of visual media and displays a corresponding affordance.

Abstract: Embodiments of the present disclosure present devices, methods, and computer readable medium for disambiguating clustered location identifiers. A location identifier can be the name of a business or establishment. Digital assets contain a plurality of metadata that can be used to identify the location or establishment at which digital assets were captured. Techniques can use various types contextual information based on a category of the digital asset for disambiguation. Automatically labelling the digital assets assists a user in organizing and sharing the digital assets with friends and family. Users can search for digital assets by the name of the location where the digital assets were captured.

Abstract: The present disclosure generally relates to retrieving and displaying contextually-relevant media content. In some embodiments, a device receives a request to display contextually-relevant media and, in response, displays a representation of a collection of media items relevant to a context of the device. In some embodiments, a device displays a visual media item of a sequence of items and, in response to receiving a swipe gesture, displays a detail user interface comprising related content for the media item. In some embodiments, a device, while displaying a first detail user interface, displays an affordance corresponding to a plurality of individuals identified as having attended a first event, that when selected, causes display of visual media corresponding to a plurality of events attended by the individuals. In some embodiments, a device, in response to user input, obtains an automatically-generated collection of visual media and displays a corresponding affordance.

Abstract: In some implementations, a computing device may create a semantic mapping that includes identified features that appear in a particular percentage of assets in a subset of assets of a media library. Also, the computing device may analyze assets of the media library using the semantic mapping to generate semantic scores, which may be used to determine a first tier of assets from the media library that rate highest for semantic score out of all assets. The computing device may present at least one of the first tier assets prominently in a user interface when viewing assets of the media library.

Abstract: The present disclosure generally relates to retrieving and displaying contextually-relevant media content. In some embodiments, a device receives a request to display contextually-relevant media and, in response, displays a representation of a collection of media items relevant to a context of the device. In some embodiments, a device displays a visual media item of a sequence of items and, in response to receiving a swipe gesture, displays a detail user interface comprising related content for the media item. In some embodiments, a device, while displaying a first detail user interface, displays an affordance corresponding to a plurality of individuals identified as having attended a first event, that when selected, causes display of visual media corresponding to a plurality of events attended by the individuals. In some embodiments, a device, in response to user input, obtains an automatically-generated collection of visual media and displays a corresponding affordance.

Abstract: Systems, methods, and computer-readable media for defining a collection of media content items of a media library for a relevant interest are provided.

Abstract: In some implementations, a computing device may create a semantic mapping that includes identified features that appear in a particular percentage of assets in a subset of assets of a media library. Also, the computing device may analyze assets of the media library using the semantic mapping to generate semantic scores, which may be used to determine a first tier of assets from the media library that rate highest for semantic score out of all assets. The computing device may present at least one of the first tier assets prominently in a user interface when viewing assets of the media library.

Abstract: Systems, methods, and computer-readable media for determining at least one valid mood for a collection of media content items of a media library are provided.

Abstract: Devices, methods, and non-transitory program storage devices (NPSDs) are disclosed herein to provide for the privacy-respectful learning of iconic scenes and places, wherein the learning is based on information received from one or more client devices in response to one or more collection criteria specified as part of one or more collection operations launched by a server device. In some embodiments, differential privacy techniques (such as the submission of predetermined amounts of noise-injecting, e.g., randomly-generated, data in conjunction with actual data) are employed by the client devices, such that any insights learned by the server device only relate to “hot spots,” “themes,” or other scenes, objects, and/or topics that are highly popular and captured in the digital assets (DAs) of many users, ensuring there is no way for the server device to learn or glean any insights related to particular users of individual client devices participating in the collection operations.

Abstract: In some implementations, a computing device may generate a day view, month views, and year view that show cards specific to each view. The cards include images, videos, and/or other assets from a media library that reflect a corresponding time frame of the card on which the assets are displayed. A selected view is presented in a graphical user interface (GUI) for interaction with a user of the media library. Upon selection of an asset displayed to the GUI, the view is switched to show more assets from a time frame similar to the selected asset while maintaining a focus on the selected asset.

Abstract: Techniques for suggesting media assets, the technique including: requesting a set of candidate media assets for a set of user media items based on a knowledge graph metadata network describing the set of user media items; receiving metadata for the set of candidate media assets; determining one or more sets of ranked media assets based on the received metadata; and outputting the determined one or more sets of ranked media assets.

Abstract: The present disclosure generally relates to retrieving and displaying contextually-relevant media content. In some embodiments, a device receives a request to display contextually-relevant media and, in response, displays a representation of a collection of media items relevant to a context of the device. In some embodiments, a device displays a visual media item of a sequence of items and, in response to receiving a swipe gesture, displays a detail user interface comprising related content for the media item. In some embodiments, a device, while displaying a first detail user interface, displays an affordance corresponding to a plurality of individuals identified as having attended a first event, that when selected, causes display of visual media corresponding to a plurality of events attended by the individuals. In some embodiments, a device, in response to user input, obtains an automatically-generated collection of visual media and displays a corresponding affordance.