Semantic Image Fill at High Resolutions
    21.
    发明公开

    公开(公告)号:US20230360376A1

    公开(公告)日:2023-11-09

    申请号:US17744995

    申请日:2022-05-16

    Applicant: Adobe Inc.

    CPC classification number: G06V10/7753 G06V10/235 G06T3/4046

    Abstract: Semantic fill techniques are described that support generating fill and editing images from semantic inputs. A user input, for example, is received by a semantic fill system that indicates a selection of a first region of a digital image and a corresponding semantic label. The user input is utilized by the semantic fill system to generate a guidance attention map of the digital image. The semantic fill system leverages the guidance attention map to generate a sparse attention map of a second region of the digital image. A semantic fill of pixels is generated for the first region based on the semantic label and the sparse attention map. The edited digital image is displayed in a user interface.

    Adding color to digital images
    23.
    发明授权

    公开(公告)号:US11232607B2

    公开(公告)日:2022-01-25

    申请号:US16751959

    申请日:2020-01-24

    Applicant: Adobe Inc.

    Abstract: In implementations of adding color to digital images, an image colorization system can display a digital image to be color adjusted in an image editing interface and convert pixel content of the digital image to a LAB color space. The image colorization system can determine a lightness value (L) in the LAB color space of the pixel content of the digital image at a specified point on the digital image, and determine colors representable in an RGB color space based on combinations of A,B value pairs with the lightness value (L) in the LAB color space. The image colorization system can then determine a range of the colors for display in a color gamut in the image editing interface, the range of the colors corresponding to the A,B value pairs with the lightness value (L) of the pixel content at the specified point on the digital image.

    Determining Image Handle Locations
    24.
    发明申请

    公开(公告)号:US20200219304A1

    公开(公告)日:2020-07-09

    申请号:US16823874

    申请日:2020-03-19

    Applicant: Adobe Inc.

    Abstract: Systems and techniques are described for determining image handle locations. An image is provided to a neural network as input, and the neural network translates the input image to an output image that includes clusters of pixels against a background that have intensities greater than an intensity of the background and that indicate candidate handle locations. Intensities of clusters of pixels in an output image are compared to a threshold intensity level to determine a set of the clusters of pixels satisfying an intensity constraint. The threshold intensity level can be user-selectable, so that a user can control a density of handles. A handle location for each cluster of the set of clusters is determined from a centroid of each cluster. Handle locations include a coordinate for the handle location and an attribute classifying a degree of freedom for a handle at the handle location.

    Digital Media Environment for Intuitive Modifications of Digital Graphics

    公开(公告)号:US20200066038A1

    公开(公告)日:2020-02-27

    申请号:US16674931

    申请日:2019-11-05

    Applicant: Adobe Inc.

    Abstract: Techniques for intuitive modifications of digital graphics in a digital media environment are described. For example, a digital graphics creation system accesses vector artwork including a vector object, such as a Bezier curve. The digital graphics creation system receives user inputs, including a user input defining handles on the vector object and a user input interacting with the handles indicating a desired change to the vector object. The digital graphics creation system modifies the vector artwork, including the vector object, by accounting for topology of the vector object and maintaining connections between connected segments of the vector object. The digital graphics creation system outputs the modified vector artwork, including the vector object, such as in a user interface.

    Determining Image Handle Locations
    26.
    发明申请

    公开(公告)号:US20200005511A1

    公开(公告)日:2020-01-02

    申请号:US16022387

    申请日:2018-06-28

    Applicant: Adobe Inc.

    Abstract: Systems and techniques are described for determining image handle locations. An image is provided to a neural network as input, and the neural network translates the input image to an output image that includes clusters of pixels against a background that have intensities greater than an intensity of the background and that indicate candidate handle locations. Intensities of clusters of pixels in an output image are compared to a threshold intensity level to determine a set of the clusters of pixels satisfying an intensity constraint. The threshold intensity level can be user-selectable, so that a user can control a density of handles. A handle location for each cluster of the set of clusters is determined from a centroid of each cluster. Handle locations include a coordinate for the handle location and an attribute classifying a degree of freedom for a handle at the handle location.

    Generating A Triangle Mesh For An Image Represented By Curves

    公开(公告)号:US20190279406A1

    公开(公告)日:2019-09-12

    申请号:US16427005

    申请日:2019-05-30

    Applicant: Adobe Inc.

    Abstract: Systems and techniques are described herein for generating a triangle mesh for an image represented by curves (e.g., Bezier segments). An outline of an image is determined and reduced to a set of connected polylines that are efficiently represented in an edge list. A triangle mesh is generated based on the edge list, rather than by directly sampling the curves of the image and using the samples as vertices of triangles. Thus, the triangle mesh is generated with a number of triangles independent from a number of curves representing the image. Samples of the curves are bound to the triangle mesh by representing the samples with barycentric coordinates with respect to a triangle in the mesh. Hence, once a mesh is deformed, locations of the samples are determined from the barycentric coordinates and triangles in the deformed mesh, and used to reconstruct the curves of the deformed image.

    DIGITAL IMAGE RADIAL PATTERN DECODING SYSTEM
    28.
    发明公开

    公开(公告)号:US20240346621A1

    公开(公告)日:2024-10-17

    申请号:US18301398

    申请日:2023-04-17

    Applicant: Adobe Inc.

    CPC classification number: G06T3/60 G06T3/40 G06T5/20 G06T5/70

    Abstract: A digital image radial pattern decoding system is described. In one example, an unfolded digital image is formed by the radial pattern decoding system by unfolding a radial pattern in a digital image. An inflated digital image is then generated by the radial pattern decoding system by upsampling the unfolded radial pattern. A grid pattern is determined by the radial pattern decoding system based on the inflated digital image. A radial pattern cell is then generated based on a reverse transform of the grid pattern. A visual pattern is generated by the radial pattern decoding system based on the radial pattern cell.

    Automated Digital Tool Identification from a Rasterized Image

    公开(公告)号:US20220254076A1

    公开(公告)日:2022-08-11

    申请号:US17170401

    申请日:2021-02-08

    Applicant: Adobe Inc.

    Abstract: A visual lens system is described that identifies, automatically and without user intervention, digital tool parameters for achieving a visual appearance of an image region in raster image data. To do so, the visual lens system processes raster image data using a tool region detection network trained to output a mask indicating whether the digital tool is useable to achieve a visual appearance of each pixel in the raster image data. The mask is then processed by a tool parameter estimation network trained to generate a probability distribution indicating an estimation of discrete parameter configurations applicable to the digital tool to achieve the visual appearance. The visual lens system generates an image tool description for the parameter configuration and incorporates the image tool description into an interactive image for the raster image data. The image tool description enables transfer of the digital tool parameter configuration to different image data.

    DENOISING IMAGES RENDERED USING MONTE CARLO RENDERINGS

    公开(公告)号:US20220148135A1

    公开(公告)日:2022-05-12

    申请号:US17093852

    申请日:2020-11-10

    Applicant: Adobe Inc.

    Abstract: A plurality of pixel-based sampling points are identified within an image, wherein sampling points of a pixel are distributed within the pixel. For individual sampling points of individual pixels, a corresponding radiance vector is estimated. A radiance vector includes one or more radiance values characterizing light received at a sampling point. A first machine learning module generates, for each pixel, a corresponding intermediate radiance feature vector, based on the radiance vectors associated with the sampling points within that pixel. A second machine learning module generates, for each pixel, a corresponding final radiance feature vector, based on an intermediate radiance feature vector for that pixel, and one or more other intermediate radiance feature vectors for one or more other pixels neighboring that pixel. One or more kernels are generated, based on the final radiance feature vectors, and applied to corresponding pixels of the image, to generate a lower noise image.

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