Embedding an input image to a diffusion model

Fine-tuning a diffusion model on a single target image with text prompts ensures consistent image variations that retain the target's identity, addressing the diversity issue in diffusion models and enhancing output quality.

AU2023226758B2Pending Publication Date: 2026-07-09ADOBE INC
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Patent Information

Application Number
AU2023226758
Authority / Receiving Office
AU · AU
Patent Type
Applications
Current Assignee / Owner
Priority Date
2022-11-08
Filing Date
2023-09-08
Publication Date
2026-07-09

AI Technical Summary

Technical Problem

Diffusion models generate diverse outputs despite detailed descriptions due to stochastic noise, failing to consistently produce images resembling a target image.

Method used

Fine-tuning a diffusion model on a single target image to embed the input image in a latent text embedding space and generate variations that retain the target image's identity, incorporating text prompts for specific edits.

Benefits of technology

Produces consistent image variations that maintain the target image's characteristics while allowing for text-based modifications, reducing training time and enhancing output quality with multiple options.

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Abstract

2023226758 08 2023 Sep 1 / FIG. 1 110 115 100 105 120 Input Image Output Image A! !with! a!mustache" Input Prompt + 20 23 22 67 58 0 8 Se p 20 23 1 / 13 110 120 Output Image 115 "A person with many + a mustache" Input Prompt Input Image 105 100 FIG. 1 1 / 13 2023226758 08 120 115 + 100
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