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公开(公告)号:US20230131321A1
公开(公告)日:2023-04-27
申请号:US17452217
申请日:2021-10-25
Applicant: Adobe Inc.
Inventor: Matthew David FISHER , Vineet BATRA , Sumit DHINGRA , Praveen Kumar DHANUKA , Deepali ANEJA , Ankit PHOGAT
Abstract: A computer-implemented method including receiving an input image at a first image stage and receiving a request to generate a plurality of variations of the input image at a second image stage. The method including generating, using an auto-regressive generative deep learning model, the plurality of variations of the input image at the second image stage and outputting the plurality of variations of the input image at the second image stage.
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公开(公告)号:US20240062455A1
公开(公告)日:2024-02-22
申请号:US17889168
申请日:2022-08-16
Applicant: Adobe Inc.
Inventor: Ankit PHOGAT , Xin SUN , Vineet BATRA , Sumit DHINGRA , Nathan A. CARR , Milos HASAN
CPC classification number: G06T15/10 , G06T17/205 , G06T11/20
Abstract: Embodiments are disclosed for performing 3-D vectorization. The method includes obtaining a three-dimensional rendered image and a camera position. The method further includes obtaining a triangle mesh representing the three-dimensional rendered image. The method further involves creating a reduced triangle mesh by removing one or more triangles from the triangle mesh. The method further involves subdividing each triangle of the reduced triangle mesh into one or more subdivided triangles. The method further involves performing a mapping of each pixel of the three-dimensional rendered image to the reduced triangle mesh. The method further involves assigning a color value to each vertex of the reduced triangle mesh. The method further involves sorting each triangle of the reduced triangle mesh using a depth value of each triangle. The method further involves generating a two-dimensional triangle mesh using the sorted triangles of the reduced triangle mesh.
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公开(公告)号:US20220414936A1
公开(公告)日:2022-12-29
申请号:US17359221
申请日:2021-06-25
Applicant: Adobe Inc.
Inventor: Vineet BATRA , Sumit DHINGRA , Matthew FISHER , Ankit PHOGAT
Abstract: Embodiments are disclosed for generating multiple color theme variations from an input image using learned color distributions. A method of generating multiple color theme variations from an input image using learned color distributions includes obtaining, by a user interface manager, an input image, determining, by a color extraction manager, one or more color priors based on the input image, generating, by a color distribution modeling network, a plurality of color theme variations based on the one or more color priors, ranking, by a color theme evaluation network, the plurality of color theme variations, and generating, by a recolor manager, a plurality of recolored output images using the plurality of color theme variations.
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