Adobe, Inc.

Jane Elizabeth Hoffswell

Ryan A Rossi

Eunyee Koh

Fan Du

Shunan Guo

Chen Chen

Trung Huu Bui

Jennifer Anne Healey

Sungchul Kim

Atanu Ranjan Sinha

Sonali Surange

Cuong D Nguyen

Vasanthi Holtcamp

Nathan Carl Ross

Saurabh Mahapatra

John Anderson

Chang Xiao

Arpit Ajay Narechania

Bingjie Xu

Fayokemi Ojo

Hyeok Kim

Yeuk Yin Chan

In some examples, an augmented reality (AR) server receives instructional data to be rendered in AR. The AR rendering server extracts multiple instruction steps from the instructional data and determines multiple spatial identifiers associated with the multiple instruction steps respectively. The multiple spatial identifiers correspond to multiple spatial objects in a real-world environment. The AR rendering server then generates AR rendering data for displaying the multiple instruction steps on an AR device at selected locations associated with the multiple spatial objects in the real-world environment. The AR rendering data is then transmitted to the AR device.

Rendering and anchoring instructional data in augmented reality with context awareness

Embodiments of the present invention provide systems, methods, and computer storage media for generating and recommending responsive visualizations. In an example embodiment, a design specification of a source visualization and an author's preferences are used to identify and rank compatible sets of candidate responsive transformations (e.g., using answer set programming). Each set is evaluated and ranked according to one or more cost metrics that quantify changes in information density, messaging, or popularity. Some embodiments generate a transformation specification in a declarative grammar that represent the sets of candidate responsive transformations independent of the structure of the source visualization specifications, compile each declarative transformation specification into a rendering grammar specification, and generate a responsive visualization by compiling the rendering grammar specification using a rendering grammar compiler. In some embodiments, the highest ranked responsive visualizations are presented as authoring recommendations and/or the highest ranked responsive visualization is automatically selected and applied.

Recommender for responsive visualization transformations

Embodiments provide systems, methods, and computer storage media for management, assessment, navigation, and/or discovery of data based on data quality, consumption, and/or utility metrics. Data may be assessed using attribute-level and/or record-level metrics that quantify data: 'quality'—the condition of data (e.g., presence of incorrect or incomplete values), its “consumption”—the tracked usage of data in downstream applications (e.g., utilization of attributes in dashboard widgets or customer segmentation rules), and/or its “utility”—a quantifiable impact resulting from the consumption of data (e.g., revenue or number of visits resulting from marketing campaigns that use particular datasets, storage costs of data). This data assessment may be performed at different stages of a data intake, preparation, and/or modeling lifecycle. For example, an interactive tree view may visually represent a nested attribute schema and attribute quality or consumption metrics to facilitate discovery of bad data before ingesting into a data lake.

Interactive tree representing attribute quality or consumption metrics for data ingestion and other applications

Systems and methods for data analysis are described. Embodiments of the present disclosure data analysis include displaying, via a data analysis interface, a data visualization in a first region of the data analysis interface; and displaying, via the data analysis interface, an analysis thread visualization in a second region of the data analysis interface. The analysis thread visualization depicts an analysis thread graph including a first node corresponding to the data visualization and an edge corresponding to an analysis path between the first node and a second node.

Generating data insights

The present disclosure relates to systems, methods, and non-transitory computer readable media that utilize a graph neural network to generate data recommendations. The disclosed systems generate a digital graph representation comprising user nodes corresponding to users, data attribute nodes corresponding to data attributes, and edges reflecting historical interactions between the users and the data attributes; Moreover, the disclosed systems generate, utilizing a graph neural network, user embeddings for the user nodes and data attribute embeddings for the data attribute nodes from the digital graph representation. In addition, the disclosed systems generate, utilizing a graph neural network, user embeddings for the user nodes and data attribute embeddings for the data attribute nodes from the digital graph representation. Furthermore, the disclosed systems determine a data recommendation for a target user utilizing the data attribute embeddings and a target user embedding corresponding to the target user from the user embeddings.

Utilizing a graph neural network to generate visualization and attribute recommendations

In implementations of augmented reality systems for comparing physical objects, a computing device implements a comparison system to detect physical objects and physical markers depicted in frames of a digital video captured using an image capture device and displayed in a user interface. The comparison system associates a physical object of the physical objects with a physical marker of the physical markers based on an association distance estimated using two-dimensional coordinates of the user interface corresponding to a center of the physical object and a distance from the image capture device to the physical marker. Characteristics of the physical object are determined that are not displayed in the user interface based on an identifier of the physical marker. The comparison system generates a virtual object for display in the user interface that includes indications of a subset of the characteristics of the physical object.

Augmented reality systems for comparing physical objects

Growing community of inventors

Seattle, WA, United States of America

Jane Elizabeth Hoffswell