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公开(公告)号：US20240257407A1
公开(公告)日：2024-08-01
申请号：US18102121
申请日：2023-01-27
Applicant: Salesforce, Inc.
Inventor： Amir Hossein Raffiee , Keld Lundgaard , Zhichao Wang
CPC classification number: G06T11/00 , G06N20/00 , G06V40/168
Abstract: Systems and methods are provided for detecting, at a face detection model of a server, a face of a person having a first identity in an image. A face recognition model of the server may detect an identity vector for the detected face of the person in the image. A new identity vector may be generated based on at least the detected identity vector. A revised image may be generated using the generated new identity vector and the image to be output for display, where the face of the person having the first identity in the image has a second identity in the revised image based on the generated new identity vector. The server may transmit the revised image.
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公开(公告)号：US11593975B2
公开(公告)日：2023-02-28
申请号：US17751862
申请日：2022-05-24
Applicant: Salesforce, Inc.
Inventor： Michael Sollami , Amir Hossein Raffiee , Owen Winne Schoppe
Abstract: A server of a generative adversarial network (GAN) for color selection; generates 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.
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公开(公告)号：US20220284641A1
公开(公告)日：2022-09-08
申请号：US17751862
申请日：2022-05-24
Applicant: Salesforce, Inc.
Inventor： Michael Sollami , Amir Hossein Raffiee , Owen Winne Schoppe
Abstract: Systems and method are provided for 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.
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