Automatically generating labeled synthetic documents

US11238312B2 · kind B2 · utility

Assignee

• Adobe Inc. · US

Inventors

• Verena Kaynig-Fittkau · Cambridge, US
• Sruthi Madapoosi Ravi · Chennai, IN
• Richard Cohn · Mill Valley, US
• Nikolaos Barmpalios · Palo Alto, US
• Michael Kraley · Lexington, US
• Kanchana Sethu · Foxborough, US

Key dates

• Filing date: Nov 21, 2019
• Grant date: Feb 1, 2022
• Expiry date: Feb 7, 2040

Classification

• Technology area (CPC G): Physics
• CPC primary: G06N3/084
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

The present disclosure relates to systems, methods, and non-transitory computer readable media for generating diverse and realistic synthetic documents using deep learning. In particular, the disclosed systems can utilize a trained neural network to generate realistic image layouts comprising page elements that comply with layout parameters. The disclosed systems can also generate synthetic content corresponding to the page elements within the image layouts. The disclosed systems insert the synthetic content into the corresponding page elements of documents based on the image layouts to generate synthetic documents.