Provided herein are method, apparatus, and computer program products for facilitating a learning user interface. The interface may be presented as a plurality of dynamic icons representing a plurality of items. The interface may be facilitated by receiving, by a processor, a selection indication associated with one item of the plurality of dynamic icons. The interface may be facilitated by determining, via the processor, at least one suggested item of the plurality of items based on the selection indication. The interface may also be facilitated by determining a visual bias for at least one suggested dynamic icon representing the at least one suggested item relative to at least one secondary dynamic icon and may be facilitated by applying the visual bias, via the interface, to the at least one suggested dynamic icon.

A garment marketplace maintains a population of stored garments, and each of those garments is associated with a display image and a characteristic vector representing characteristics of the garment. The garment marketplace receives an intake garment and obtains a classification image of the intake garment. A garment identification system determines whether the intake garment is the same as one of the stored garments. To do so, the garment identification system applies a garment identification model to the classification image. The model generates a characteristic vector representing the intake garment. If the characteristic vector for the intake vector is the same as a characteristic vector for a stored garment, the garment identification system determines the intake garment is the same as the stored garment.

Top attributes of a product are identified from text content of an electronic document and are presented as visual depictions of the attributes. The attributes are identified and ranked based on the text content, such as whether the text content describes the attribute in a positive or negative manner. Top attributes are selected from the ranking and a visual depiction of the top attributes is identified. The visual depiction can be a universally recognized symbol or a custom image designated to an attribute. The visual depiction is superimposed on the text content associated with the attributes when the electronic document is presented at a display. In this way, top attributes for a product can be presented in a manner that condenses the relevant information provided by the electronic document into a format better suited for providing the information on small screens of mobile devices.

Technologies for 3D virtual environment placement of 3D models based on 2D images are disclosed. At least an outline of a 3D virtual environment may be generated. A 2D image of one or more 2D images may be identified. A first product from the first 2D image may be identified. At least one 3D model of one or more 3D models based, at least, on the first product may be determined. A first location for placement of the first product in the 3D virtual environment may be identified. The at least one 3D model may be added within the 3D virtual environment based, at least, on the first location. The 3D virtual environment may be rendered into a visually interpretable form. A second product may be identified from the first 2D image, forming a first grouping of products. A starting element for the first grouping of products may be determined.

A garment production system, comprising a virtual development environment configured to receive and store in a database thereof body information relating to a user, establish measurements for the user based on the body information, display, on a display device connected to the virtual development environment, a virtual representation of the user using the established measurements, customize one or more garments for the user based on the established measurements, display, on the display device, a virtual representation of the one or more customized garments on the virtual representation of the user, receive and store in the database personalization information from the user regarding the one or more customized garments, and alter the one or more customized garments and the virtual representation thereof based on the received personalization information for manufacture thereof.

A method for providing similar or related products based on deep-learning, which is performed by a data processing unit of a shopping mall server, includes: acquiring an item image and item information for an item registered in a shopping mall; detecting bounding boxes for one or more objects by object-detecting the item image; setting a bounding box for an object associated with the item based on the item information; creating a main bounding box image by cropping a portion of the item image in the set bounding box; creating a padding image by padding-processing the main bounding box image; extracting a feature vector for the padding image; matching the feature vector with the item and storing the feature vector in a database; and creating the database for a similar or related product search service.

A method and apparatus provide a virtual clothing wearing service based on deep-learning. A virtual clothing wearing server based on deep-learning includes a communicator configured to receive a user image and a v clothing image; a memory configured to store a program including first and second deep-learning models; a processor configured to generate an image of virtually dressing a virtual wearing clothing on a user. The program is configured to: generate, by the first deep-learning model, a transformed virtual wearing clothing image by transforming the virtual wearing clothing image in accordance with a body of the user in the user image based on the user image and the virtual wearing clothing image, and generate, by the second deep-learning model, the virtual wearing person image by dressing the transformed virtual wearing clothing on the body of the user based on the user image and the transformed virtual wearing clothing image.

An apparatus, computer program product, and method are provided for predictive recommendations of device rendered objects using one or more objective models. In the context of a method, the method generates, for each device rendered object of a plurality of device rendered objects, a multiple objective score. The method also determines a real-time adjustment factor based in part on a received objective adjustment signal and generates, for each device rendered object of the plurality of device rendered objects, an adjusted multiple objective score based on the real-time adjustment factor. The method also generate a ranked device rendered object set, selects a subset of the ranked rendered object set, and transmits the ranked device rendered object subset to a client device associated with the user object of the user object objective, the subset configured for rendering within the user, interface area of the client device.

Techniques for an item swap feature are described herein. A user interface may be presented where the user interface includes a plurality of user interface elements. A first area of the user interface may include one or more user interface elements which correspond to item information for an item. A second area of the user interface may include one or more user interface elements which correspond to one or more recommended items. A first interact with a swap feature associated with a particular user interface of the one or more user interface elements of the recommended items may be received. The particular user interface may be associated with a particular item. The user interface may be updated to present item information for the particular item, the recommended items and corresponding user interface elements may be updated, and the particular item may be added to a checkout cart user interface element.

Systems for simulating joining operations, such as welding, are disclosed. In some examples, a system may use a desktop device for conducting welding simulations, such as for purposes of training In some examples, the system may additionally, or alternatively, use modular workpieces. In some examples, the system may additionally, or alternatively, conduct the welding simulation based on one or more selected pieces of welding equipment.