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公开(公告)号：US20230086807A1
公开(公告)日：2023-03-23
申请号：US17723879
申请日：2022-04-19
Applicant: Adobe Inc. , Czech Technical University in Prague
Inventor： Michal LUKÁC , Elya SHECHTMAN , Daniel SÝKORA , David FUTSCHIK
Abstract: Embodiments are disclosed for segmented image generation. The method may include receiving an input image and a segmentation mask, projecting, using a differentiable machine learning pipeline, a plurality of segments of the input image into a plurality of latent spaces associated with a plurality of generators to obtain a plurality of projected segments, and compositing the plurality of projected segments into an output image.
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公开(公告)号：US20230162443A1
公开(公告)日：2023-05-25
申请号：US17534225
申请日：2021-11-23
Applicant: Adobe Inc.
Inventor： Chi Cheng HSU , Michal LUKÁC , Michael GHARBI , Kevin WAMPLER
CPC classification number: G06T17/20 , G06T11/203
Abstract: Embodiments are disclosed for receiving a target shape. The method may further include initializing a gradient mesh to a vector graphic having at least one node. The method may further include performing a constrained optimization of the vector graphic based on the target shape. The method may further include generating a stress metric based on a comparison of the constrained optimization and the target shape. The method may further include determining one or more unconstrained candidate vector graphics based on the stress metric. The method may further include selecting an improved vector graphic from the one or more unconstrained candidate vector graphics. The method may further include mapping the vector graphic to the improved vector graphic. The method may further include optimizing the improved vector graphic based on the target shape.
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公开(公告)号：US20240087089A1
公开(公告)日：2024-03-14
申请号：US17901583
申请日：2022-09-01
Applicant: Adobe Inc.
Inventor： Souymodip CHAKRABORTY , Vineet BATRA , Michal LUKÁC , Matthew David FISHER , Ankit PHOGAT
CPC classification number: G06T3/60 , G06T5/20 , G06T2207/10024 , G06T2207/20076
Abstract: Embodiments are disclosed for reconstructing linear gradients from an input image that can be applied to another image. In particular, in one or more embodiments, the disclosed systems and methods comprise receiving a raster image, the raster image including a representation of a linear color gradient. The disclosed systems and methods further comprise determining a vector representing a direction of the linear color gradient. The disclosed systems and methods further comprise analyzing pixel points along the direction of the linear color gradient to compute color stops of the linear color gradient. The disclosed systems and methods further comprise generating an output color gradient vector with the computed color stops of the linear color gradient, the output color gradient vector to be applied to a vector graphic.
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公开(公告)号：US20230070666A1
公开(公告)日：2023-03-09
申请号：US17466711
申请日：2021-09-03
Applicant: Adobe Inc. , Czech Technical University in Prague
Inventor： Michal LUKÁC , Daniel SÝKORA , David FUTSCHIK , Zhaowen WANG , Elya SHECHTMAN
Abstract: Embodiments are disclosed for translating an image from a source visual domain to a target visual domain. In particular, in one or more embodiments, the disclosed systems and methods comprise a training process that includes receiving a training input including a pair of keyframes and an unpaired image. The pair of keyframes represent a visual translation from a first version of an image in a source visual domain to a second version of the image in a target visual domain. The one or more embodiments further include sending the pair of keyframes and the unpaired image to an image translation network to generate a first training image and a second training image. The one or more embodiments further include training the image translation network to translate images from the source visual domain to the target visual domain based on a calculated loss using the first and second training images.
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