The present disclosure relates to systems, methods, and non-transitory computer readable media for accurately and flexibly identifying digital images with similar style to a query digital image using fine-grain style determination via weakly supervised style extraction neural networks. For example, the disclosed systems can extract a style embedding from a query digital image using a style extraction neural network such as a novel two-branch autoencoder architecture or a weakly supervised discriminative neural network. The disclosed systems can generate a combined style embedding by combining complementary style embeddings from different style extraction neural networks. Moreover, the disclosed systems can search a repository of digital images to identify digital images with similar style to the query digital image. The disclosed systems can also learn parameters for one or more style extraction neural network through weakly supervised training without a specifically labeled style ontology for sample digital images.

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.

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.

Systems and methods for digitally fetching music content may include (1) providing a user of a device with a music service accessible via the device, (2) receiving a digital user request to (i) select a music composition based on a digital image corresponding to one or more music compositions and (ii) digitally fetch the music composition for use via the music service, and, in response to receiving the digital user request, (3) analyzing the digital image and selecting the music composition based on the analysis of the digital image, and (4) digitally fetching the music composition for use via the music service. Various other methods, systems, and computer-readable media are also disclosed.

Systems and methods for digitally fetching music content may include (1) providing a user of a device with a music service accessible via the device, (2) receiving a digital user request to (i) select a music composition based on a digital image corresponding to one or more music compositions and (ii) digitally fetch the music composition for use via the music service, and, in response to receiving the digital user request, (3) analyzing the digital image and selecting the music composition based on the analysis of the digital image, and (4) digitally fetching the music composition for use via the music service. Various other methods, systems, and computer-readable media are also disclosed.

An image retrieval method, an image retrieval device, and an image retrieval system, which are used for image retrieval, are provided. The image retrieval method comprises: receiving a first original image (S100); extracting an image feature of the first original image to obtain a first feature code (S200); obtaining first target information according to the first feature code (S300); according to the first target information, searching for a first target painting set corresponding to the first target information in at least one of a painting library and a knowledge graph library, so as to obtain the first target painting set (S400); and outputting the first target painting set (S500).

An image retrieval method, an image retrieval device, and an image retrieval system, which are used for image retrieval, are provided. The image retrieval method comprises: receiving a first original image (S100); extracting an image feature of the first original image to obtain a first feature code (S200); obtaining first target information according to the first feature code (S300); according to the first target information, searching for a first target painting set corresponding to the first target information in at least one of a painting library and a knowledge graph library, so as to obtain the first target painting set (S400); and outputting the first target painting set (S500).

A method includes receiving, from an image capture device in communication with the data processing hardware, image data for an area of interest of a user. The method also includes receiving a query from the user referring to one or more objects detected within the image data and requesting a digital assistant to discern insights associated with the one or more objects referred to by the query. The method also includes processing the query and the image data to: identify, based on context data extracted from the image data, the one or more objects referred to by the query; and determine the insights associated with the identified one or more objects for the digital assistant to discern. The method also includes generating, for output from a user device associated with the user, content indicating the discerned insights associated with the identified one or more objects.