Generating physically-based material maps

    公开(公告)号:US11663775B2

    公开(公告)日:2023-05-30

    申请号:US17233861

    申请日:2021-04-19

    Applicant: ADOBE INC.

    CPC classification number: G06T15/506 G06N3/08 G06T15/005 G06T15/04

    Abstract: Methods, system, and computer storage media are provided for generating physical-based materials for rendering digital objects with an appearance of a real-world material. Images depicted the real-world material, including diffuse component images and specular component images, are captured using different lighting patterns, which may include area lights. From the captured images, approximations of one or more material maps are determined using a photometric stereo technique. Based on the approximations and the captured images, a neural network system generates a set of material maps, such as a diffuse albedo material map, a normal material map, a specular albedo material map, and a roughness material map. The material maps from the neural network may be optimized based on a comparison of the input images of the real-world material and images rendered from the material maps.

    GENERATING PHYSICALLY-BASED MATERIAL MAPS

    公开(公告)号:US20220335682A1

    公开(公告)日:2022-10-20

    申请号:US17233861

    申请日:2021-04-19

    Applicant: ADOBE INC.

    Abstract: Methods, system, and computer storage media are provided for generating physical-based materials for rendering digital objects with an appearance of a real-world material. Images depicted the real-world material, including diffuse component images and specular component images, are captured using different lighting patterns, which may include area lights. From the captured images, approximations of one or more material maps are determined using a photometric stereo technique. Based on the approximations and the captured images, a neural network system generates a set of material maps, such as a diffuse albedo material map, a normal material map, a specular albedo material map, and a roughness material map. The material maps from the neural network may be optimized based on a comparison of the input images of the real-world material and images rendered from the material maps.

    UTILIZING HEMISPHERICAL CLAMPING FOR IMPORTANCE SAMPLING OF IMAGE-BASED LIGHT TO RENDER A VIRTUAL ENVIRONMENT

    公开(公告)号:US20220335677A1

    公开(公告)日:2022-10-20

    申请号:US17233910

    申请日:2021-04-19

    Applicant: Adobe Inc.

    Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods that utilize hemispherical clamping for importance sampling of an image-based light (IBL) to generate a digital image of a virtual environment. For example, the disclosed systems identify a hemispherical portion of an IBL image that corresponds to a reflective surface location on a virtual object. The disclosed systems can then clamp the IBL image using one or more importance sampling algorithms to exclude portions of the IBL image outside of the hemispherical portion that do not contribute direct lighting onto the reflective surface location. The disclosed systems can further utilize the one or more importance sampling algorithms to efficiently sample a ray direction between the reflective surface location and the hemispherical portion of the IBL image. In certain embodiments, the disclosed systems use the sampled ray direction to generate a digital image rendering portraying the virtual object.

    GENERATING PROCEDURAL MATERIALS FROM DIGITAL IMAGES

    公开(公告)号:US20210343051A1

    公开(公告)日:2021-11-04

    申请号:US16863540

    申请日:2020-04-30

    Applicant: Adobe Inc.

    Abstract: The present disclosure relates to using end-to-end differentiable pipeline for optimizing parameters of a base procedural material to generate a procedural material corresponding to a target physical material. For example, the disclosed systems can receive a digital image of a target physical material. In response, the disclosed systems can retrieve a differentiable procedural material for use as a base procedural material in response. The disclosed systems can compare a digital image of the base procedural material with the digital image of the target physical material using a loss function, such as a style loss function that compares visual appearance. Based on the determined loss, the disclosed systems can modify the parameters of the base procedural material to determine procedural material parameters for the target physical material. The disclosed systems can generate a procedural material corresponding to the base procedural material using the determined procedural material parameters.

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