In accordance with the present invention, an interactive user display application is provided. The application displays and refreshes images that are intended to represent users or members of a social network or other web-based service. Using these images, the interactive user display application allows a user of the application to interact with other users or their profiles while viewing their images or while interacting with or consuming media.

In one embodiment, one or more computing systems may receive an indication of a first location of a first mobile-client system of a first user associated with an online social network. The one or more computing systems may identify one or more second users from among a plurality of users associated with the online social network based on one or more notification rules. Each identified second user may be associated with a second mobile-client system having a second location within a threshold distance of the first location and may be within a threshold degree of separation of the first user on the online social network. The one or more computing systems may send a first notification to the first mobile-client system of the first user. The first notification may reference one or more of the identified second users.

Computer systems and associated methods are disclosed to implement a model development environment (MDE) that allows a team of users to perform iterative model experiments to develop machine learning (ML) media models. In embodiments, the MDE implements a media data management interface that allows users to annotate and manage training data for models. In embodiments, the MDE implements a model experimentation interface that allows users to configure and run model experiments, which include a training run and a test run of a model. In embodiments, the MDE implements a model diagnosis interface that displays the model's performance metrics and allows users to visually inspect media samples that were used during the model experiment to determine corrective actions to improve model performance for later iterations of experiments. In embodiments, the MDE allows different types of users to collaborate on a series of model experiments to build an optimal media model.

Computer systems and associated methods are disclosed to implement a model development environment (MDE) that allows a team of users to perform iterative model experiments to develop machine learning (ML) media models. In embodiments, the MDE implements a media data management interface that allows users to annotate and manage training data for models. In embodiments, the MDE implements a model experimentation interface that allows users to configure and run model experiments, which include a training run and a test run of a model. In embodiments, the MDE implements a model diagnosis interface that displays the model's performance metrics and allows users to visually inspect media samples that were used during the model experiment to determine corrective actions to improve model performance for later iterations of experiments. In embodiments, the MDE allows different types of users to collaborate on a series of model experiments to build an optimal media model.

Systems, methods, devices, media, and computer-readable instructions are described for local image tagging and processing in a resource-constrained environment such as a mobile device. In some embodiments, characteristics associated with images are used to determine whether to store content (e.g., images and video clips) as ephemeral content or non-ephemeral content. Based on the determination, the image is stored in a non-ephemeral camera roll storage of the mobile device, or an ephemeral local application storage. Additional storage operations such as encryption or backup copying may additionally be determined and performed based on the analysis of the content. In some embodiments, such images may be indexed, sorted, and searched based on the image tagging operations used to characterize the content.

In embodiments of event image curation, a computing device includes memory that stores a collection of digital images associated with a type of event, such as a digital photo album of digital photos associated with the event, or a video of image frames and the video is associated with the event. A curation application implements a convolutional neural network, which receives the digital images and a designation of the type of event. The convolutional neural network can then determine an importance rating of each digital image within the collection of the digital images based on the type of the event. The importance rating of a digital image is representative of an importance of the digital image to a person in context of the type of the event. The convolutional neural network generates an output of representative digital images from the collection based on the importance rating of each digital image.

Provided is an avatar service system and method that are provided through a network. The avatar service system may include a request receiving unit to receive a request for an avatar to perform an action, a data extracting unit to extract metadata and image data corresponding to the request from the database storing the metadata with respect to the action of the avatar and the image data for a plurality of layers forming the avatar, and an avatar action processing unit to generate and provide action data for applying, to the avatar, the action of the avatar corresponding to the request using the extracted metadata and the extracted image data.

An apparatus and method to adjust item recommendations are disclosed herein. A first image attribute of a query image is compared to a second image attribute of each of a plurality of inventory images of a plurality of inventory items to identify the inventory items similar to the query image. Item recommendations comprising the identified inventory items in a first listing order are provided for display at a remote device. A second listing order of the identified inventory items is determined based on a user preference for a particular one of the identified inventory items. At least the second listing order is provided to the remote device for re-display of the item recommendations in accordance with the second listing order.

Examples of techniques for detecting and tracking virtual containers are disclosed. In one example implementation according to aspects of the present disclosure, a computer-implemented method includes detecting a virtual container. The method further includes collecting virtual container data for the virtual container. The method also includes associating, by a processing device, the virtual container to at least one of a plurality of images. Additionally, the method includes building, by the processing device, a container event database based on the virtual container data and the association of the virtual container to the at least one of the plurality of images, so as to enable tracking of software in the plurality of images and in live virtual containers.

A method includes receiving, at a mobile device, a selection of a first media item transferred from the mobile device to a remote device. The method also includes selecting, by the mobile device, a second media item to transfer to the remote device based on a similarity of the second media item to the first media item. The method further includes generating, by the mobile device, packaged moment data to transfer to the remote device, where the packaged moment data includes media data associated with multiple media items including the first media item and the second media item.