Multi-layer lighting source with textured lighting gel layer

    公开(公告)号:US11321889B1

    公开(公告)日:2022-05-03

    申请号:US17082378

    申请日:2020-10-28

    Applicant: Adobe Inc.

    Abstract: A multi-layer light source includes an emissive layer and a textured lighting gel layer, the lighting gel layer being situated between the emissive layer and a 2D canvas or a 3D object. User inputs controlling the multi-layer light source are received, these user inputs being provided with the user interacting with the 2D canvas without switching to editing in 3D space. The multi-layer light source is configured based on the user inputs and, based on the configuration, emission of light rays from the multi-layer light source is determined. Areas of shadows cast by 3D objects are also determined. An image generation system determines, a color of a location (e.g., a pixel) on the 2D canvas or the 3D object that a light ray intersects based on the color that is in the lighting gel layer that the light ray passes through.

    Generative shape creation and editing

    公开(公告)号:US11037341B1

    公开(公告)日:2021-06-15

    申请号:US16744105

    申请日:2020-01-15

    Applicant: Adobe Inc.

    Abstract: Generative shape creation and editing is leveraged in a digital medium environment. An object editor system represents a set of training shapes as sets of visual elements known as “handles,” and converts sets of handles into signed distance field (SDF) representations. A handle processor model is then trained using the SDF representations to enable the handle processor model to generate new shapes that reflect salient visual features of the training shapes. The trained handle processor model, for instance, generates new sets of handles based on salient visual features learned from the training handle set. Thus, utilizing the described techniques, accurate characterizations of a set of shapes can be learned and used to generate new shapes. Further, generated shapes can be edited and transformed in different ways.

    ENHANCED TEXTURE PACKING
    14.
    发明申请

    公开(公告)号:US20190180495A1

    公开(公告)日:2019-06-13

    申请号:US16273938

    申请日:2019-02-12

    Applicant: ADOBE INC.

    Abstract: Embodiments of the present invention are directed towards compactly incorporating texture charts into a texture atlas. Texture charts represent three-dimensional mesh segments flattened into two-dimensional shapes. In one embodiment, a texture atlas generating engine is used to generate and evaluate compactness scores of candidate placements for a texture chart. Candidate placements generally refer to the possible locations where a texture chart can be incorporated into a texture atlas. The compactness score can be based on minimizing the distance between a texture chart being incorporated into the texture atlas and the center of mass of previously incorporated texture charts within a texture atlas. In embodiments, an infinity norm can be utilized to compute such a compactness score by outputting an average length of vectors between a texture chart being incorporated into a texture atlas and the texture atlas. Other embodiments may be described and/or claimed.

    Rendering images from deeply learned raytracing parameters

    公开(公告)号:US10902665B2

    公开(公告)日:2021-01-26

    申请号:US16368548

    申请日:2019-03-28

    Applicant: ADOBE INC.

    Abstract: Images are rendered from deeply learned raytracing parameters. Active learning, via a machine learning (ML) model (e.g., implemented by a deep neural network), is used to automatically determine, infer, and/or predict optimized, or at least somewhat optimized, values for parameters used in raytracing methods. Utilizing deep learning to determine optimized, or at least somewhat optimized, values for raytracing parameters is in contrast to conventional methods, which require users to rely of heuristics for parameter value setting. In various embodiments, one or more parameters regarding the termination and splitting of traced light paths in stochastic-based (e.g., Monte Carlo) raytracing are determined via active learning. In some embodiments, one or more parameters regarding the sampling rate of shadow rays are also determined.

    Drawing Curves in Space Guided by 3-D Objects

    公开(公告)号:US20200250865A1

    公开(公告)日:2020-08-06

    申请号:US16855328

    申请日:2020-04-22

    Applicant: Adobe Inc.

    Abstract: Various embodiments enable curves to be drawn around 3-D objects by intelligently determining or inferring how the curve flows in the space around the outside of the 3-D object. The various embodiments enable such curves to be drawn without having to constantly rotate the 3-D object. In at least some embodiments, curve flow is inferred by employing a vertex position discovery process, a path discovery process, and a final curve construction process.

    Drawing curves in space guided by 3-D objects

    公开(公告)号:US10657682B2

    公开(公告)日:2020-05-19

    申请号:US15485980

    申请日:2017-04-12

    Applicant: Adobe Inc.

    Abstract: Various embodiments enable curves to be drawn around 3-D objects by intelligently determining or inferring how the curve flows in the space around the outside of the 3-D object. The various embodiments enable such curves to be drawn without having to constantly rotate the 3-D object. In at least some embodiments, curve flow is inferred by employing a vertex position discovery process, a path discovery process, and a final curve construction process.

    Light path correlation in digital image rendering of a digital scene

    公开(公告)号:US10445926B2

    公开(公告)日:2019-10-15

    申请号:US15403903

    申请日:2017-01-11

    Applicant: Adobe Inc.

    Abstract: Techniques and systems are described that support light path correlation in digital image rendering of a digital scene. In one example, a plurality of light paths between a light source and the digital image to be rendered of a digital scene are identified by a computing device. Each light path of the plurality of light paths includes a primary vertex and a secondary vertex between respective segments of the light path. A plurality of correlated samples is then generated by the computing device from the light paths. Each correlated sample of the plurality of correlated samples is based at least in part on similarity of the secondary vertex of respective said light paths to each other, e.g., on location, geometric normal, or surface material properties. The digital image of the digital scene is then rendered by the computing device based at least in part on the plurality of correlated samples.

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