IP Library Granted Patent US 11,373,343
Granted Patent B2
US 11,373,343 · App. 17/091,259 · Granted Jun 28, 2022

Systems and methods of generating color palettes with a generative adversarial network

Inventors: Michael Sollami (Cambridge, MA); Amir Hossein Raffiee (Cambridge, MA); Owen Winne Schoppe (Orinda, CA)
Assignee: Salesforce, Inc.
G06T11/001G06K9/6218G06K9/6256G06T7/90G06V10/751G06T2207/10024G06T2207/20081G06T2207/20084
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Quick Facts
Patent No.
US 11,373,343
App. No.
17/091,259
Granted
Jun 28, 2022
Kind
B2
Abstract

Generating, at a server of a generative adversarial network (GAN) for color selection, a training set of color palettes. A color palette generator of the server generates a first set of color palettes based on the training set of color palettes. The first set of color palettes may be compared with a reference set of color palettes to predict a curated set of color palettes. Colors from the curated set of color palettes may be removed that are within a predetermined distance from one another in a color space. The GAN may be validated by performing cluster analysis to determine outlier latent dimensions to be changed for the color selection by the GAN. Proposed color palettes may be generated based on the GAN to be displayed on a display device.

Claims (30)

1. A method comprising:

generating, at a server of a generative adversarial network (GAN) for color selection, a training set of color palettes, wherein one or more colors of the set of color palettes is at least one selected from the group consisting of: a cluster of colors, colors of a website, or colors of an image;

generating, at a color palette generator of the server, a first set of color palettes based on the training set of color palettes;

comparing, at a color sequence discriminator of the server, the first set of color palettes with a reference set of color palettes to predict a curated set of color palettes;

removing, at the server, colors from the curated set of color palettes that are within a predetermined distance from one another in a color space;

validating, at the server, the GAN by performing a cluster analysis to determine outlier latent dimensions to be changed for the color selection by the GAN; and

generating, at the server using the validated GAN, proposed color palettes to be displayed on a display device.

2. The method of claim 1 , wherein the validating further comprises:

inspecting, at the server, the determined outlier latent dimensions; and

changing one or more of the dimensions for the color selection by the GAN based on the inspection.

3. The method of claim 2 , wherein the inspecting the determined outlier latent dimensions further comprises:

generating, at the server, cluster maps to determine the outlier dimensions.

4. The method of claim 1 , wherein the generating the proposed color palettes further comprises:

generating, at the color palette generator, the proposed color palettes based on a color palette to be completed and random input color sequences.

5. The method of claim 1 , wherein the generating the proposed color palettes further comprises:

generating, at the color palette generator, the proposed color palettes based on at least one received color characteristic and random input color sequences,

wherein the at least one received color characteristic is selected from the group consisting of: hue, saturation, brightness, or color temperature.

6. A system comprising:

a server having a processor and a memory to store a generative adversarial network (GAN) for color selection to:

generate, at a server of a generative adversarial network (GAN) for color selection, a training set of color palettes, wherein one or more colors of the set of color palettes is at least one selected from the group consisting of: a cluster of colors, colors of a website, or colors of an image;

generate, at a color palette generator of the server, a first set of color palettes based on the training set of color palettes;

compare, at a color sequence discriminator of the server, the first set of color palettes with a reference set of color palettes to predict a curated set of color palettes;

removing, at the server, colors from the curated set of color palettes that are within a predetermined distance from one another in a color space;

validate, at the server, the GAN by performing a cluster analysis to determine outlier latent dimensions to be changed for the color selection by the GAN; and

generate, at the server using the validated GAN, proposed color palettes to be displayed on a display device.

7. The system of claim 6 , wherein the server validates the GAN by inspecting the determined outlier latent dimensions, and changing one or more of the dimensions for the color selection by the GAN based on the inspection.

8. The system of claim 7 , wherein the server inspects the determined outlier latent dimensions by generating cluster maps to determine the outlier dimensions.

9. The system of claim 6 , wherein the color palette generator generates the proposed color palettes based on a color palette to be completed and random input color sequences.

10. The system of claim 6 , wherein the color palette generator generates the proposed color palettes based on at least one received color characteristic and random input color sequences, and

wherein the at least one received color characteristic is selected from the group consisting of: hue, saturation, brightness, or color temperature.

Assignments (2)
CHANGE OF NAME Recorded Dec 18, 2024
From: SALESFORCE.COM, INC.
To: SALESFORCE, INC.
Reel/Frame 069717/0507 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 6, 2020
From: SOLLAMI, MICHAEL; RAFFIEE, AMIR HOSSEIN; SCHOPPE, OWEN WINNE
To: SALESFORCE.COM, INC.
Reel/Frame 054296/0864 →
Cited By (1)
US 12,493,998