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US Patent 10382799 Real-time synthetically generated video from still frames

Patent 10382799 was granted and assigned to Capital One on August, 2019 by the United States Patent and Trademark Office.

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Contents

Patent abstractTimelineTable: Further ResourcesReferences
Is a
Patent
Patent

Patent attributes

Patent Applicant
Capital One
Capital One
Current Assignee
Capital One
Capital One
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
10382799
Date of Patent
August 13, 2019
Patent Application Number
16173374
Date Filed
October 29, 2018
Patent Citations Received
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US Patent 12125008 Systems and methods for managing a financial account in a low-cash mode
3
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US Patent 12014339 Systems and methods for electronic database communications
4
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US Patent 12020223 Systems and methods for managing a financial account in a low-cash mode
5
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US Patent 12026451 Methods and systems for generating alternative content using generative adversarial networks implemented in an application programming interface layer
6
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US Patent 11537506 System for visually diagnosing machine learning models
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US Patent 11238341 Efficient encoding and decoding sequences using variational autoencoders
‌
US Patent 11551429 Photorealistic image simulation with geometry-aware composition
‌
US Patent 11544499 Classification of synthetic data tasks and orchestration of resource allocation
...
Patent Primary Examiner
‌
Diane M Wills
Patent abstract

Systems and methods for generating synthetic video are disclosed. For example, a system may include a memory unit and a processor configured to execute the instructions to perform operations. The operations may include receiving video data, normalizing image frames, generating difference images, and generating an image sequence generator model. The operations may include training an autoencoder model using difference images, the autoencoder comprising an encoder model and a decoder model. The operations may include identifying a seed image frame and generating a seed difference image from the seed image frame. The operations may include generating, by the image sequence generator model, synthetic difference images based on the seed difference image. In some aspects, the operations may include using the decoder model to synthetic normalized image frames from the synthetic difference images. The operations may include generating synthetic video by adding background to the synthetic normalized image frames.

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