SYSTEMS AND METHODS FOR IMAGE COMPOSITING

    公开(公告)号:US20250022099A1

    公开(公告)日:2025-01-16

    申请号:US18351838

    申请日:2023-07-13

    Applicant: ADOBE INC.

    Abstract: Systems and methods for image compositing are provided. An aspect of the systems and methods includes obtaining a first image and a second image, wherein the first image includes a target location and the second image includes a target element; encoding the second image using an image encoder to obtain an image embedding; generating a descriptive embedding based on the image embedding using an adapter network; and generating a composite image based on the descriptive embedding and the first image using an image generation model, wherein the composite image depicts the target element from the second image at the target location of the first image.

    UTILIZING MACHINE LEARNING MODELS TO GENERATE REFINED DEPTH MAPS WITH SEGMENTATION MASK GUIDANCE

    公开(公告)号:US20230326028A1

    公开(公告)日:2023-10-12

    申请号:US17658873

    申请日:2022-04-12

    Applicant: Adobe Inc.

    CPC classification number: G06T7/11 G06T2207/20084 G06T7/50 G06T7/215

    Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for utilizing machine learning models to generate refined depth maps of digital images utilizing digital segmentation masks. In particular, in one or more embodiments, the disclosed systems generate a depth map for a digital image utilizing a depth estimation machine learning model, determine a digital segmentation mask for the digital image, and generate a refined depth map from the depth map and the digital segmentation mask utilizing a depth refinement machine learning model. In some embodiments, the disclosed systems generate first and second intermediate depth maps using the digital segmentation mask and an inverse digital segmentation mask and merger the first and second intermediate depth maps to generate the refined depth map.

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