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公开(公告)号：US20240386627A1
公开(公告)日：2024-11-21
申请号：US18319808
申请日：2023-05-18
Applicant: Adobe Inc.
Inventor： Ambareesh Revanur , Debraj Debashish Basu , Shradha Agrawal , Dhwanit Agarwal , Deepak Pai
Abstract: In accordance with the described techniques, an image transformation system receives an input image and a text prompt, and leverages a generator network to edit the input image based on the text prompt. The generator network includes a plurality of layers configured to perform respective edits. A plurality of masks are generated based on the text prompt that define local edit regions, respectively, of the input image for respective layers of the generator network. Further, the generator network generates an edited image by editing the input image based on the plurality of masks, the respective edits of the respective layers, and the text prompt.
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公开(公告)号：US20240312087A1
公开(公告)日：2024-09-19
申请号：US18360919
申请日：2023-07-28
Applicant: ADOBE INC.
Inventor： Shradha Agrawal , Debraj Debashish Basu , Deepak Pai , Nimish Srivastav , Meghanath Macha , Ambareesh Revanur
IPC: G06T11/60 , G06F40/186 , G06F40/40 , G06Q30/0241 , G06T7/90
CPC classification number: G06T11/60 , G06F40/186 , G06F40/40 , G06Q30/0276 , G06T7/90 , G06T2207/10024 , G06T2207/20081
Abstract: Systems and methods for document processing are provided. One aspect of the systems and methods includes identifying a theme and an input image of a product. Another aspect of the systems and methods includes generating an output image depicting the product and the theme based on the input image using an image generation model that is trained to generate images consistent with a brand. Another aspect of the systems and methods includes generating text based on the product and the theme using a text generation model. Another aspect of the systems and methods includes generating custom content consistent with the brand and the theme based on the output image and the text.
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公开(公告)号：US11176713B2
公开(公告)日：2021-11-16
申请号：US16778906
申请日：2020-01-31
Applicant: ADOBE INC.
Inventor： Shradha Agrawal , Deepak Pai , Dhanya Raghu
Abstract: Embodiments of the present disclosure are directed towards generating images conditioned on a desired attribute. In particular, an attribute-based image generation system can use a directional-GAN architecture to generate images conditioned on a desired attribute. A latent vector and a desired attribute are received. A feature subspace is determined for the latent vector using a latent-attribute linear classifier trained to determine a relationship between the latent vector and the desired attribute. An image is generated using the latent vector such that the image contains the desired attribute. In embodiments, where the feature space differs from a desired feature subspace, a directional vector is applied to the latent vector that shifts the latent vector from the feature subspace to the desired feature subspace. This modified latent vector is then used during generation of the image.
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公开(公告)号：US20210241497A1
公开(公告)日：2021-08-05
申请号：US16778906
申请日：2020-01-31
Applicant: ADOBE INC.
Inventor： Shradha Agrawal , Deepak Pai , Dhanya Raghu
Abstract: Embodiments of the present disclosure are directed towards generating images conditioned on a desired attribute. In particular, an attribute-based image generation system can use a directional-GAN architecture to generate images conditioned on a desired attribute. A latent vector and a desired attribute are received. A feature subspace is determined for the latent vector using a latent-attribute linear classifier trained to determine a relationship between the latent vector and the desired attribute. An image is generated using the latent vector such that the image contains the desired attribute. In embodiments, where the feature space differs from a desired feature subspace, a directional vector is applied to the latent vector that shifts the latent vector from the feature subspace to the desired feature subspace. This modified latent vector is then used during generation of the image.
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