Technologies are provided to supply image assets for presentation at a client device. Some embodiments include a computing device that can determine that multiple image assets to be presented in a user interface are unavailable within a non-volatile storage device of the computing device. The computing device can then generate a request for an image sprite containing the multiple image assets, and can send the request to a content source platform. The request identifies the multiple image assets. The computing device can receive, from the content source platform, the image sprite and metadata corresponding to the image sprite. The metadata defines attributes of the multiple image assets. The computing device can store the metadata in the non-volatile storage device, and can extract, using the metadata, the multiple image assets from the image sprite. The computing device can present the multiple assets during presentation of the user interface.

Technologies are provided to supply image assets for presentation at a client device. Some embodiments include a computing device that can determine that multiple image assets to be presented in a user interface are unavailable within a non-volatile storage device of the computing device. The computing device can then generate a request for an image sprite containing the multiple image assets, and can send the request to a content source platform. The request identifies the multiple image assets. The computing device can receive, from the content source platform, the image sprite and metadata corresponding to the image sprite. The metadata defines attributes of the multiple image assets. The computing device can store the metadata in the non-volatile storage device, and can extract, using the metadata, the multiple image assets from the image sprite. The computing device can present the multiple assets during presentation of the user interface.

A system for selecting an image to accompany text from a user in connection with a social media post. The system is capable of receiving text from the user, identifying one or more search terms based on the text, identifying candidate images from images in one or more image databases using the search terms, presenting one or more candidate images to the user, receiving from the user a selected image from the one or more candidate images, generating the social media post comprising the selected image and the user-submitted text, and transmitting the social media post for display.

An augmented reality (AR) overlay augments traditional menu items with corresponding photos, thereby facilitating a decision-making process of a user ordering from the menu. In addition to providing imagery of the menu items listed, other information may also be supplied, such as ratings, reviews etc. In this regard, users can visualize what to expect before ordering, and can order with a greater degree of confidence that they will enjoy the menu item they select.

Provided is a method of image searching based on artificial intelligence (AI), the method including acquiring retrieved information, which includes at least one of a retrieved image and an image address, and a user query on the basis of a search result of an image search engine, detecting a keyword-category combination on the basis of a type of the acquired user query, determining whether cache data that matches the detected keyword-category combination exists, generating, in response to absence of the cache data that matches the keyword-category combination, an object-category combination through an AI technology based object detection on the acquired retrieved information.

Provided is a method of image searching based on artificial intelligence (AI), the method including acquiring retrieved information, which includes at least one of a retrieved image and an image address, and a user query on the basis of a search result of an image search engine, detecting a keyword-category combination on the basis of a type of the acquired user query, determining whether cache data that matches the detected keyword-category combination exists, generating, in response to absence of the cache data that matches the keyword-category combination, an object-category combination through an AI technology based object detection on the acquired retrieved information.

A contextual filter system configured to perform operations that include, capturing an image frame at a client device, wherein the image frame includes a depiction of an object, identifying an object category of the object based on the depiction of the object within the image frame, accessing media content associated with the object category within a media repository, generating a presentation of the media content, and causing display of the presentation of the media content within the image frame at the client device.

A contextual filter system configured to perform operations that include, capturing an image frame at a client device, wherein the image frame includes a depiction of an object, identifying an object category of the object based on the depiction of the object within the image frame, accessing media content associated with the object category within a media repository, generating a presentation of the media content, and causing display of the presentation of the media content within the image frame at the client device.

In one embodiment, an apparatus comprises a memory and a processor. The memory is to store visual data associated with a visual representation captured by one or more sensors. The processor is to: obtain the visual data associated with the visual representation captured by the one or more sensors, wherein the visual data comprises uncompressed visual data or compressed visual data; process the visual data using a convolutional neural network (CNN), wherein the CNN comprises a plurality of layers, wherein the plurality of layers comprises a plurality of filters, and wherein the plurality of filters comprises one or more pixel-domain filters to perform processing associated with uncompressed data and one or more compressed-domain filters to perform processing associated with compressed data; and classify the visual data based on an output of the CNN.

In one embodiment, an apparatus comprises a memory and a processor. The memory is to store visual data associated with a visual representation captured by one or more sensors. The processor is to: obtain the visual data associated with the visual representation captured by the one or more sensors, wherein the visual data comprises uncompressed visual data or compressed visual data; process the visual data using a convolutional neural network (CNN), wherein the CNN comprises a plurality of layers, wherein the plurality of layers comprises a plurality of filters, and wherein the plurality of filters comprises one or more pixel-domain filters to perform processing associated with uncompressed data and one or more compressed-domain filters to perform processing associated with compressed data; and classify the visual data based on an output of the CNN.