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US Patent 11907839 Detail-preserving image editing techniques

Patent 11907839 was granted and assigned to Adobe Inc. on February, 2024 by the United States Patent and Trademark Office.

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Is a
Patent
Patent
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Patent attributes

Patent Applicant
Adobe Inc.
Adobe Inc.
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Current Assignee
Adobe Inc.
Adobe Inc.
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
119078390
Patent Inventor Names
Jakub Fiser0
Aliakbar Darabi0
Alexandru Vasile Costin0
Jingwan Lu0
Kevin Wampler0
Ratheesh Kalarot0
Elya Shechtman0
Date of Patent
February 20, 2024
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Patent Application Number
174685110
Date Filed
September 7, 2021
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Patent Citations
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US Patent 11227187 Generating artificial intelligence solutions using raw data and simulated data
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US Patent 11354792 System and methods for modeling creation workflows
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US Patent 11494667 Systems and methods for improved adversarial training of machine-learned models
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US Patent 11521362 Messaging system with neural hair rendering
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US Patent 11544880 Generating modified digital images utilizing a global and spatial autoencoder
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US Patent 11557022 Neural network system with temporal feedback for denoising of rendered sequences
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US Patent 11580673 Methods, systems, and computer readable media for mask embedding for realistic high-resolution image synthesis
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US Patent 11610435 Generative adversarial neural network assisted video compression and broadcast
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...
Patent Citations Received
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US Patent 11983628 Attribute control techniques for image editing
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Patent Primary Examiner
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Katrina R Fujita
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CPC Code
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G06T 5/20
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G06T 11/001
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G06T 11/60
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G06T 2207/10024
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G06T 2207/20081
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G06T 2207/20084
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G06T 2207/20221
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G06T 2210/22
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Patent abstract

Systems and methods combine an input image with an edited image generated using a generator neural network to preserve detail from the original image. A computing system provides an input image to a machine learning model to generate a latent space representation of the input image. The system provides the latent space representation to a generator neural network to generate a generated image. The system generates multiple scale representations of the input image, as well as multiple scale representations of the generated image. The system generates a first combined image based on first scale representations of the images and a first value. The system generates a second combined image based on second scale representations of the images and a second value. The system blends the first combined image with the second combined image to generate an output image.

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