Light estimation method for three-dimensional (3D) rendered objects

    公开(公告)号:US12299810B2

    公开(公告)日:2025-05-13

    申请号:US17846918

    申请日:2022-06-22

    Applicant: Snap Inc.

    Abstract: A method for applying lighting conditions to a virtual object in an augmented reality (AR) device is described. In one aspect, the method includes generating, using a camera of a mobile device, an image, accessing a virtual object corresponding to an object in the image, identifying lighting parameters of the virtual object based on a machine learning model that is pre-trained with a paired dataset, the paired dataset includes synthetic source data and synthetic target data, the synthetic source data includes environment maps and 3D scans of items depicted in the environment map, the synthetic target data includes a synthetic sphere image rendered in the same environment map, applying the lighting parameters to the virtual object, and displaying, in a display of the mobile device, the shaded virtual object as a layer to the image.

    DOMAIN CHANGES IN GENERATIVE ADVERSARIAL NETWORKS

    公开(公告)号:US20250037436A1

    公开(公告)日:2025-01-30

    申请号:US18911590

    申请日:2024-10-10

    Applicant: Snap Inc.

    Abstract: An image manipulation system for generating modified images using a generative adversarial network (GAN) trains GANs using domain changes, aligns input images with generated images, classifies and associates target images based on a symmetry, and uses a modified discriminator structure. A method for domain changes includes generating, using a pre-trained GAN trained on a plurality of first target images, a plurality of images, and determining a feature for each of the plurality of images. The method further includes determining the feature for each of a plurality of second target images and matching, based on the feature, second target images of the plurality of second target images with the plurality of images. The method further includes training a discriminator of the pre-trained GAN with the second target images and the plurality of images.

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