# US 2025/0165710 A1 · Method and analysis device thereof for analyzing degree of correlation between image generated by generative model and text prompt

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- Number: US 2025/0165710 A1
- Document ID: US20250165710A1
- Status: Published application
- Kind: A1
- Application number: 18/815,057
- Filed: 2024-08-26
- Published: 2025-05-22
- Earliest claimed: 2023-11-21
- Assignees: Electronics and Telecommunications Research Institute
- Applicants: Electronics and Telecommunications Research Institute
- Inventors: Sung-Won MOON; Do-Won NAN; Wonyoung YOO; Jung Soo LEE; Jiwon LEE
- Web page: https://patentgrep.com/patent/US20250165710A1

## CPC

- G06F 40/279: Recognition of textual entities
- G06F 40/40: Processing or translation of natural language (natural language analysis G06F40/20; semantic analysis G06F40/30)
- G06T 7/11: Region-based segmentation
- G06T 11/00: Two-dimensional [2D] image generation
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL

## Abstract

A method and an analysis device thereof for analyzing a degree of correlation between an image generated by a generative model and a text prompt are proposed. The method includes receiving the text prompt by an analysis device, inputting the text prompt into the text-to-image generative model by the analysis device, calculating, by the analysis device, degrees of correlation between text elements in the text prompt and conditional latent vectors for each text element, and determining, by the analysis device, at least one text element among the text elements for generating the image if the degrees of correlation for the at least on text element is greater than a threshold value, wherein the conditional latent vectors are generated in a process of generating the image by the text-to-image generative model.

## Claims

### Claim 1

A method for analyzing a degree of correlation between an image and a text prompt, which are generated by a generative model, the method comprising:
receiving the text prompt by an analysis device;
inputting the text prompt into the text-to-image generative model by the analysis device;
calculating, by the analysis device, degrees of correlation between text elements in the text prompt and conditional latent vectors for each text element; and
determining, by the analysis device, at least one text element among the text elements for generating the image if the degrees of correlation for the at least on text element is greater than a threshold value,
wherein the conditional latent vectors are generated in a process of generating the image by the text-to-image generative model.

### Claim 2 (depends on 1)

The method of claim 1, wherein the text-to-image generative model is a Stable Diffusion model.

### Claim 3 (depends on 1)

The method of claim 1, wherein the analysis device calculates the degrees of correlation on the basis of attention maps generated by performing cross attention between the conditional latent vectors and the at least one text element.

### Claim 4 (depends on 1)

The method of claim 1, wherein the analysis device calculates the degrees of correlation on the basis of attention maps generated by performing cross attention between text embeddings generated by a text encoder receiving the text prompt in the process of generating the image and the conditional latent vectors generated conditional on the text embeddings.

### Claim 5 (depends on 3)

The method of claim 3, wherein the analysis device distinguishes or segments an area where the at least one text element is positioned in the image on the basis of the attention maps.

### Claim 6

An analysis device for analyzing a degree of correlation between an image and a text prompt, the analysis device comprising:
an interface device configured to receive input of the text prompt;
a storage device configured to store a text-to-image generative model for generating an image on the basis of text information; and
a calculation device configured to select at least one text element among the text elements in the text prompt based on degrees of correlation between conditional latent vectors and the at least one text element, wherein the conditional latent vectors are generated in a process of generating the image by the text-to-image generative model which input the text prompt.

### Claim 7 (depends on 6)

The analysis device of claim 6, the text-to-image generative model is a Stable Diffusion model.

### Claim 8 (depends on 6)

The analysis device of claim 6, wherein the calculation device calculates the degrees of correlation on the basis of attention maps generated by performing cross attention between the conditional latent vectors and the at least one text element.

### Claim 9 (depends on 6)

The analysis device of claim 6, wherein the calculation device calculates the degrees of correlation on the basis of attention maps generated by performing cross attention between text embeddings generated by a text encoder receiving the text prompt in a process of generating the image and conditional latent vectors generated conditional on the text embeddings.

### Claim 10 (depends on 8)

The analysis device of claim 8, wherein the calculation device distinguishes or segments an area where the at least one text element is positioned in the image on the basis of the attention maps.