Ebay, Incorporated

Qiaosong Wang

Robinson Piramuthu

Fan Yang

Mohammadhadi Kiapour

Ajinkya Gorakhnath Kale

Shuai Zheng

Japjit Singh Tulsi

Jinrong Xie

Andrew Chalkley

Bindia Saraf

James Thomas Dowdell

Vignesh Jagadeesh

Jean-David Ruvini

Ethan Benjamin Rubinson

Bryan Kent Ressler

Dileep Kumar Basam

Kevin Shude Lin

Mahyar Najibikohnehshahri

Wen Zheng

Fang Fang

Antonio Haro

Thomas F Dittmer

Xiaotong Wu

Allison Carol Allain

Nitzan Mekel

An-Ti Chiang

Ankit Grover

Robert Charles Clemmons

Display screen or portion thereof with transitional graphical user interface

Systems, methods, and computer program products for identifying a candidate product in an electronic marketplace based on a visual comparison between candidate product image visual content and input query image visual content. Embodiments generate and store descriptive image signatures from candidate product images or selected portions of such images. A subsequently calculated visual similarity measure serves as a visual search result score for the candidate product in comparison to an input query image. Any number of images of any number of candidate products may be analyzed, such as for items available for sale in an online marketplace. Image analysis results are stored in a database and made available for subsequent automated on-demand visual comparisons to an input query image. The embodiments enable substantially real time visual based product searching of a potentially vast catalog of items.

Intelligent online personal assistant with offline visual search database

A system receives image data associated with an item, where the image data comprising a view of the item from two or more angles; determines physical attributes of the item; generates a base model of the item; samples the base model to generate one or more sampled models, each of the one or more sampled models comprising a subset of the geometric data, the subset of the geometric data determined based on one or more device characteristics of one or more user devices that interface with the system; receives device characteristics of a user device associated with a request from the user device for the item; selects, based on the received device characteristics, a sampled model of the item; and transmits a data object comprising the selected sampled model to the user device to cause the user device to generate a three-dimensional rendering of the item.

Reconstruction of 3D model with immersive experience

An application server associated with an online marketplace may receive a set of images of an item, spatial information associated with each image of the set of images indicating a relative spatial location to the item for each image, and viewing direction information indicating a viewing direction relative to the item for each image. The application server may then generate a neural radiance field model of the item in a three dimensional space based on the set of images, the spatial information, and the viewing direction information, and may generate a set of spherical harmonics for the neural radiance field model based on predicting one or more spherical harmonic coefficients using the set of images, the spatial information, and the viewing direction information. The application server may then output a three dimensional model of the item generated based on the set of spherical harmonics.

Techniques for generating a three dimensional model for a listing

Disclosed are systems, methods, and non-transitory computer-readable media for using adversarial learning for fine-grained image search. An image search system receives a search query that includes an input image depicting an object. The search system generates, using a generator, a vector representation of the object in a normalized view. The generator was trained based on a set of reference images of known objects in multiple views, and feedback data received from an evaluator that indicates performance of the generator at generating vector representations of the known objects in the normalized view. The evaluator including a discriminator sub-module, a normalizer sub-module, and a semantic embedding sub-module that generate the feedback data. The image search system identifies, based on the vector representation of the object, a set of other images depicting the object, and returns at least one of the other images in response to the search query.

Adversarial learning for finegrained image search

Methods, systems, and articles of manufacture, including computer program products, are provided for image cleanup. In some embodiments, there is provide a method which may include subsampling a first image to a first level image of a multiscale transform; performing, based on a machine learning model, an identification of a foreground portion of the first level image and a background portion of the first level image; generating, based on the identification of the foreground portion and the background portion, a first mask; upscaling the first mask to a resolution corresponding to the first image depicting the foreground item; applying the upscaled first mask to the first image to form a second image depicting the foreground item; and providing the second image depicting the foreground item to a publication system. Related systems and articles of manufacture, including computer program products, are also provided.

Image cleanup on a mobile device

Camera platform techniques are described. In an implementation, a plurality of digital images and data describing times, at which, the plurality of digital images are captured is received by a computing device. Objects of clothing are recognized from the digital images by the computing device using object recognition as part of machine learning. A user schedule is also received by the computing device that describes user appointments and times, at which, the appointments are scheduled. A user profile is generated by the computing device by training a model using machine learning based on the recognized objects of clothing, times at which corresponding digital images are captured, and the user schedule. From the user profile, a recommendation is generated by processing a subsequent user schedule using the model as part of machine learning by the computing device.

Camera platform incorporating schedule and stature

Methods, systems, and computer programs are presented for adding new features to a network service. A method includes receiving an image depicting an object of interest. A category set is determined for the object of interest and an image signature is generated for the image. Using the category set and the image signature, the method identifies a set of publications within a publication database and assigns a rank to each publication. The method causes presentation of the ranked list of publications at a computing device from which the image was received.

Image analysis and prediction based visual search

The disclosed technologies include a robotic selling assistant that receives an item from a seller, automatically generates a posting describing the item for sale, stores the item until it is sold, and delivers or sends the item out for delivery. The item is placed in a compartment that uses one or more sensors to identify the item, retrieve supplemental information about the item, and take pictures of the item for inclusion in the posting. A seller-supplied description of the item may be verified based on the retrieved supplemental information, preventing mislabeled items from being sold.

Auto posting system

Systems, methods, and computer program products for identifying a relevant candidate product in an electronic marketplace. Embodiments perform a visual similarity comparison between candidate product image visual content and input query image visual content, process formal and informal natural language user inputs, and coordinate aggregated past user interactions with the marketplace stored in a knowledge graph. Visually similar items and their corresponding product categories, aspects, and aspect values can determine suggested candidate products without discernible delay during a multi-turn user dialog. The user can then refine the search for the most relevant items available for purchase by providing responses to machine-generated prompts that are based on the initial search results from visual, voice, and/or text inputs. An intelligent online personal assistant can thus guide a user to the most relevant candidate product more efficiently than existing search tools.

Intelligent online personal assistant with multi-turn dialog based on visual search

In various example embodiments, a system and method for integration of a three-dimensional model is disclosed. In one example embodiment, a method includes receiving a plurality of images, selecting points on the images and triangulating the points to generate a plurality of depth maps, generate a three-dimensional mesh by combining the plurality of depth maps, generating a three-dimensional model of the item by projecting the plurality of images onto the mesh using the points, calibrating colors used in the model using colors diffuse properties of the colors in the images, and providing a user interface allowing a user to select one or more user points on the three-dimensional model and provide additional information associated with the selected user points.

Integration of 3D models

Growing community of inventors

San Jose, CA, United States of America

Qiaosong Wang