IMAGE GENERATION METHOD, APPARATUS, ELECTRONIC DEVICE, AND STORAGE MEDIUM

    公开(公告)号:US20250157150A1

    公开(公告)日:2025-05-15

    申请号:US18941402

    申请日:2024-11-08

    Applicant: Lemon Inc.

    Abstract: Embodiments of the present disclosure disclose an image generation method, an apparatus, an electronic device, and a storage medium. The method includes: determining three-dimensional representations of preset areas in a target object according to a noise vector, wherein the three-dimensional representations are used to represent features of points in a space, and the preset areas have different size percentages in the target object; determining a three-dimensional mesh model in a target posture according to posture control parameters of the preset areas; sampling corresponding areas in the three-dimensional mesh model respectively according to camera poses for the preset areas, to obtain sampling points corresponding to the preset areas; determining target features corresponding to the sampling points according to the three-dimensional representations of the preset areas; and rendering the preset areas according to the target features, to generate target images, wherein the target images contain the target object in the target posture.

    MULTI-DIMENSIONAL IMAGE STYLIZATION USING TRANSFER LEARNING

    公开(公告)号:US20240273871A1

    公开(公告)日:2024-08-15

    申请号:US18168867

    申请日:2023-02-14

    Applicant: Lemon Inc.

    CPC classification number: G06V10/7715 G06V10/28 G06V10/454

    Abstract: A method for generating a multi-dimensional stylized image. The method includes providing input data into a latent space for a style conditioned multi-dimensional generator of a multi-dimensional generative model and generating the multi-dimensional stylized image from the input data by the style conditioned multi-dimensional generator. The method further includes synthesizing content for the multi-dimensional stylized image using a latent code and corresponding camera pose from the latent space to formulate an intermediate code to modulate synthesis convolution layers to generate feature images as multi-planar representations and synthesizing stylized feature images of the feature images for generating the multi-dimensional stylized image of the input data. The style conditioned multi-dimensional generator is tuned using a guided transfer learning process using a style prior generator.

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