Adobe Patent for Image Personalization using Diffusion Model
Summary
The USPTO has granted Adobe Inc. a patent (US12586364B2) for a system that personalizes images using a diffusion model and a style encoder. The patent covers methods for generating synthetic images that incorporate a target style identified from a style image.
What changed
The United States Patent and Trademark Office (USPTO) has granted Adobe Inc. patent US12586364B2 for a novel image processing system. This patent details a method for image personalization that utilizes a pretrained diffusion model. The system includes a style encoder network that generates a style vector from a target style image, which is then used by a diffusion model to create a synthetic image incorporating that style. The style encoder and diffusion model are trained independently.
This patent grant is primarily relevant for intellectual property management and innovation tracking within the AI and image processing sectors. While it does not impose direct compliance obligations on regulated entities, it signifies a technological advancement in AI-driven image generation and personalization. Companies operating in the AI, software, and digital media spaces, particularly those developing or utilizing diffusion models for creative applications, should be aware of this patent as it pertains to their intellectual property landscape.
Source document (simplified)
Single image concept encoder for personalization using a pretrained diffusion model
Grant US12586364B2 Kind: B2 Mar 24, 2026
Assignee
ADOBE INC.
Inventors
Saeid Motiian, Shabnam Ghadar
Abstract
Systems and methods for image processing are provided. One aspect of the systems and methods includes identifying a style image including a target style. A style encoder network generates a style vector representing the target style based on the style image. The style encoder can be trained based on a style loss that encourages the network to match a desired style. A a diffusion model generates a synthetic image that includes the target style based on the style vector. The diffusion model is trained independently of the style encoder network.
CPC Classifications
G06V 10/82 G06V 10/751 G06V 10/771 G06N 3/0464 G06N 3/08 G06T 11/001 G06T 2207/20081 G06T 2207/20084
Filing Date
2022-11-08
Application No.
18053450
Claims
19
Named provisions
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