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US Patent 11869057 Generating a digital image using a generative adversarial network

Patent 11869057 was granted and assigned to EBay on January, 2024 by the United States Patent and Trademark Office.

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Is a
Patent
Patent
0

Patent attributes

Patent Applicant
EBay
EBay
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Current Assignee
EBay
EBay
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
118690570
Patent Inventor Names
Shuai Zheng0
Omid Poursaeed0
Mohammadhadi Kiapour0
Robinson Piramuthu0
Date of Patent
January 9, 2024
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Patent Application Number
175395580
Date Filed
December 1, 2021
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Patent Citations
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US Patent 10074118 Point-and-shoot product lister
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US Patent 10210631 Generating synthetic image data
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US Patent 10552714 Generating a digital image using a generative adversarial network
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US Patent 11222246 Generating a digital image using a generative adversarial network
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US Patent 11068530 Context-based image selection for electronic media
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US Patent 8458054 Method, medium, and system for suggesting images for items without images in listings data
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US Patent 9405773 Searching for more products like a specified product
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US Patent 9721291 Identifying effective images associated with items
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Patent Primary Examiner
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Sean T Motsinger
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CPC Code
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G06Q 30/0643
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G06V 10/25
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G06V 10/20
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G06V 40/103
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G06Q 30/0625
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G06F 16/532
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G06F 16/9535
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G06F 16/5838
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Patent abstract

Various embodiments described herein utilize multiple levels of generative adversarial networks (GANs) to facilitate generation of digital images based on user-provided images. Some embodiments comprise a first generative adversarial network (GAN) and a second GAN coupled to the first GAN, where the first GAN includes an image generator and at least two discriminators, and the second GAN includes an image generator and at least one discriminator. According to some embodiments, the (first) image generator of the first GAN is trained by processing a user-provided image using the first GAN. For some embodiments, the user-provided image and the first generated image, generated by processing the user-provided image using the first GAN, are combined to produce a combined image. For some embodiments, the (second) image generator of the second GAN is trained by processing the combined image using the second GAN.

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