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    Avatar generation based on driving views
    2.
    发明授权
    Avatar generation based on driving views 有权

    公开(公告)号：US12051168B2

    公开(公告)日：2024-07-30

    申请号：US17932645

    申请日：2022-09-15

    Applicant: Lemon Inc. ,  Beijing Zitiao Network Technology Co., Ltd.

    Inventor： Hongyi Xu ,  Tao Hu ,  Linjie Luo

    IPC: G06T19/20 ,  G06T7/73 ,  G06T15/04 ,  G06T17/20

    CPC classification number: G06T19/20 ,  G06T7/75 ,  G06T15/04 ,  G06T17/20 ,  G06T2207/20084 ,  G06T2210/16 ,  G06T2219/2004

    Abstract: Systems and methods are provided that include a processor executing an avatar generation program to obtain driving view(s), calculate a skeletal pose of the user, and generate a coarse human mesh based on a template mesh and the skeletal pose of the user. The program further constructs a texture map based on the driving view(s) and the coarse human mesh, extracts a plurality of image features from the texture map, the image features being aligned to a UV map, and constructs a UV positional map based on the coarse human mesh. The program further extracts a plurality of pose features from the UV positional map, the pose features being aligned to the UV map, generates a plurality of pose-image features based on the UV map-aligned image features and UV map-aligned pose features, and renders an avatar based on the plurality of pose-image features.

    AVATAR GENERATION BASED ON DRIVING VIEWS
    4.
    发明公开
    AVATAR GENERATION BASED ON DRIVING VIEWS 审中-公开

    公开(公告)号：US20240096041A1

    公开(公告)日：2024-03-21

    申请号：US17932645

    申请日：2022-09-15

    Applicant: Lemon Inc. ,  Beijing Zitiao Network Technology Co., Ltd.

    Inventor： Hongyi Xu ,  Tao Hu ,  Linjie Luo

    IPC: G06T19/20 ,  G06T7/73 ,  G06T15/04 ,  G06T17/20

    CPC classification number: G06T19/20 ,  G06T7/75 ,  G06T15/04 ,  G06T17/20 ,  G06T2207/20084 ,  G06T2210/16 ,  G06T2219/2004

    Abstract: Systems and methods are provided that include a processor executing an avatar generation program to obtain driving view(s), calculate a skeletal pose of the user, and generate a coarse human mesh based on a template mesh and the skeletal pose of the user. The program further constructs a texture map based on the driving view(s) and the coarse human mesh, extracts a plurality of image features from the texture map, the image features being aligned to a UV map, and constructs a UV positional map based on the coarse human mesh. The program further extracts a plurality of pose features from the UV positional map, the pose features being aligned to the UV map, generates a plurality of pose-image features based on the UV map-aligned image features and UV map-aligned pose features, and renders an avatar based on the plurality of pose-image features.

    Cascaded domain bridging for image generation
    5.
    发明授权
    Cascaded domain bridging for image generation 有权

    公开(公告)号：US12299799B2

    公开(公告)日：2025-05-13

    申请号：US18046073

    申请日：2022-10-12

    Applicant: Lemon Inc. ,  Beijing Zitiao Network Technology Co., Ltd.

    Inventor： Shen Sang ,  Tiancheng Zhi ,  Guoxian Song ,  Jing Liu ,  Linjie Luo ,  Chunpong Lai ,  Weihong Zeng ,  Jingna Sun ,  Xu Wang

    IPC: G06T15/00 ,  G06T7/62 ,  G06V10/56 ,  G06V10/74 ,  G06V10/75

    Abstract: A method of generating a stylized 3D avatar is provided. The method includes receiving an input image of a user, generating, using a generative adversarial network (GAN) generator, a stylized image, based on the input image, and providing the stylized image to a first model to generate a first plurality of parameters. The first plurality of parameters include a discrete parameter and a continuous parameter. The method further includes providing the stylized image and the first plurality of parameters to a second model that is trained to generate an avatar image, receiving, from the second model, the avatar image, comparing the stylized image to the avatar image, based on a loss function, to determine an error, updating the first model to generate a second plurality of parameters that correspond to the first plurality of parameters, based on the error, and providing the second plurality of parameters as an output.

    MULTI-DIMENSIONAL IMAGE STYLIZATION USING TRANSFER LEARNING
    6.
    发明公开
    MULTI-DIMENSIONAL IMAGE STYLIZATION USING TRANSFER LEARNING 审中-公开

    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.

    Inventor： Guoxian Song ,  Hongyi Xu ,  Jing Liu ,  Tiancheng Zhi ,  Yichun Shi ,  Jianfeng Zhang ,  Zihang Jiang ,  Jiashi Feng ,  Shen Sang ,  Linjie Luo

    IPC: G06V10/77 ,  G06V10/28 ,  G06V10/44

    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.

    Cascaded domain bridging for image generation
    7.
    发明授权
    Cascaded domain bridging for image generation 有权

    公开(公告)号：US12260485B2

    公开(公告)日：2025-03-25

    申请号：US18046077

    申请日：2022-10-12

    Applicant: Lemon Inc.

    Inventor： Guoxian Song ,  Shen Sang ,  Tiancheng Zhi ,  Jing Liu ,  Linjie Luo

    IPC: G06T15/00 ,  G06T7/11 ,  G06T15/02

    Abstract: A method of generating a style image is described. The method includes receiving an input image of a subject. The method further includes encoding the input image using a first encoder of a generative adversarial network (GAN) to obtain a first latent code. The method further includes decoding the first latent code using a first decoder of the GAN to obtain a normalized style image of the subject, wherein the GAN is trained using a loss function according to semantic regions of the input image and the normalized style image.

    Agilegan-based stylization method to enlarge a style region
    8.
    发明授权
    Agilegan-based stylization method to enlarge a style region 有权

    公开(公告)号：US12190481B2

    公开(公告)日：2025-01-07

    申请号：US17807527

    申请日：2022-06-17

    Applicant: Lemon Inc.

    Inventor： Guoxian Song ,  Jing Liu ,  Weihong Zeng ,  Jingna Sun ,  Xu Wang ,  Linjie Luo

    IPC: G06T5/50 ,  G06T3/4046 ,  G06V40/16

    Abstract: Methods and systems for enlarging a stylized region of an image are disclosed that include receiving an input image, generating, using a first generative adversarial network (GAN) generator, a first stylized image, based on the input image, normalizing the input image, generating, using a second generative adversarial network (GAN) generator, a second stylized image, based on the normalized input image, blending the first stylized image and the second stylized image to obtain a third stylized image, and providing the third stylized image as an output.

    Agilegan-based refinement method and framework for consistent texture generation
    9.
    发明授权
    Agilegan-based refinement method and framework for consistent texture generation 有权

    公开(公告)号：US12169907B2

    公开(公告)日：2024-12-17

    申请号：US17534631

    申请日：2021-11-24

    Applicant: Lemon Inc.

    Inventor： Guoxian Song ,  Jing Liu ,  Chunpong Lai ,  Linjie Luo

    IPC: G06T5/50 ,  G06N3/045 ,  G06T3/00 ,  G06T3/04 ,  G06V10/774 ,  G06V10/82

    Abstract: Methods and systems for generating a texturized image are disclosed. Some examples may include: receiving an input image, receiving an exemplar texture image, generating, using an encoder, a first latent code vector representation based on the input image, generating, using a generative adversarial network generator, a second latent code vector representation based on the exemplar texture image, blending the first latent code vector representation and the second latent code vector representation to obtain a blended latent code vector representation, generating, by the GAN generator, a texturized image based on the blended latent code vector representation and providing the texturized image as an output image.

    AGILEGAN-BASED REFINEMENT METHOD AND FRAMEWORK FOR CONSISTENT TEXTURE GENERATION
    10.
    发明公开
    AGILEGAN-BASED REFINEMENT METHOD AND FRAMEWORK FOR CONSISTENT TEXTURE GENERATION 审中-公开

    公开(公告)号：US20230162320A1

    公开(公告)日：2023-05-25

    申请号：US17534631

    申请日：2021-11-24

    Applicant: Lemon Inc.

    Inventor： Guoxian Song ,  Jing Liu ,  Chunpong Lai ,  Linjie Luo

    IPC: G06T3/00 ,  G06N3/04 ,  G06T5/50

    CPC classification number: G06T3/00 ,  G06N3/0454 ,  G06T5/50

    Abstract: Methods and systems for generating a texturized image are disclosed. Some examples may include: receiving an input image, receiving an exemplar texture image, generating, using an encoder, a first latent code vector representation based on the input image, generating, using a generative adversarial network generator, a second latent code vector representation based on the exemplar texture image, blending the first latent code vector representation and the second latent code vector representation to obtain a blended latent code vector representation, generating, by the GAN generator, a texturized image based on the blended latent code vector representation and providing the texturized image as an output image.

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