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公开(公告)号：US20240135621A1
公开(公告)日：2024-04-25
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
CPC classification number: G06T15/00 , G06T7/62 , G06V10/56 , G06V10/751 , G06V10/761 , G06T2207/10024 , G06T2207/30201
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.
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公开(公告)号：US12217466B2
公开(公告)日：2025-02-04
申请号：US17519711
申请日：2021-11-05
Applicant: Lemon Inc.
Inventor： Jing Liu , Chunpong Lai , Guoxian Song , Linjie Luo
Abstract: Systems and methods directed to controlling the similarity between stylized portraits and an original photo are described. In examples, an input image is received and encoded using a variational autoencoder to generate a latent vector. The latent vector may be blended with latent vectors that best represent a face in the original user portrait image. The resulting blended latent vector may be provided to a generative adversarial network (GAN) generator to generate a controlled stylized image. In examples, one or more layers of the stylized GAN generator may be swapped with one or more layers of the original GAN generator. Accordingly, a user can interactively determine how much stylization vs. personalization should be included in a resulting stylized portrait.
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公开(公告)号：US20230124252A1
公开(公告)日：2023-04-20
申请号：US17501990
申请日：2021-10-14
Applicant: Lemon Inc.
Inventor： Jing Liu , Chunpong Lai , Guoxian Song , Linjie Luo , Ye Yuan
Abstract: Systems and method directed to generating a stylized image are disclosed. In particular, the method includes, in a first data path, (a) applying first stylization to an input image and (b) applying enlargement to the stylized image from (a). The method also includes, in a second data path, (c) applying segmentation to the input image to identify a face region of the input image and generate a mask image, and (d) applying second stylization to an entirety of the input image and inpainting to the identified face region of the stylized image. Machine-assisted blending is performed based on (1) the stylized image after the enlargement from the first data path, (2) the inpainted image from the second data path, and (3) the mask image, in order to obtain a final stylized image.
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公开(公告)号：US12148095B2
公开(公告)日：2024-11-19
申请号：US17932640
申请日：2022-09-15
Applicant: Lemon Inc.
Inventor： Tiancheng Zhi , Shen Sang , Guoxian Song , Chunpong Lai , Jing Liu , Linjie Luo
Abstract: Systems and methods for rendering a translucent object are provided. In one aspect, the system includes a processor coupled to a storage medium that stores instructions, which, upon execution by the processor, cause the processor to receive at least one mesh representing at least one translucent object. For each pixel to be rendered, the processor performs a rasterization-based differentiable rendering of the pixel to be rendered using the at least one mesh and determines a plurality of values for the pixel to be rendered based on the rasterization-based differentiable rendering. The rasterization-based differentiable rendering can include performing a probabilistic rasterization process along with aggregation techniques to compute the plurality of values for the pixel to be rendered. The plurality of values includes a set of color channel values and an opacity channel value. Once values are determined for all pixels, an image can be rendered.
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公开(公告)号：US12106545B2
公开(公告)日：2024-10-01
申请号：US17534681
申请日：2021-11-24
Applicant: LEMON INC.
Inventor： Jingna Sun , Peibin Chen , Weihong Zeng , Xu Wang , Jing Liu , Chunpong Lai , Shen Sang
IPC: G06V10/764 , G06N3/08 , G06V10/72 , G06V10/82
CPC classification number: G06V10/764 , G06N3/08 , G06V10/72 , G06V10/82
Abstract: The present disclosure provides a training method and device for an image identifying model, and an image identifying method. The training method comprises: obtaining image samples of a plurality of categories; inputting image samples of each category into a feature extraction layer of the image identifying model to extract a feature vector of each image sample; calculating a statistical characteristic information of an actual distribution function corresponding to each category according to the feature vector of each image sample of the each category; establishing an augmented distribution function corresponding to the each category according to the statistical characteristic information; obtaining augmented sample features of the each category based on the augmented distribution function; and inputting feature vectors of the image samples and the augmented sample features into a classification layer of the image identifying model for supervised learning.
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Patent Agency Ranking
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
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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公开(公告)号：US11978280B2
公开(公告)日：2024-05-07
申请号：US17529192
申请日：2021-11-17
Applicant: Lemon Inc.
Inventor： Jingna Sun , Peibin Chen , Weihong Zeng , Xu Wang , Jing Liu , Chunpong Lai , Shen Sang
IPC: G06K9/46 , G06F18/21 , G06F18/2113 , G06F18/22 , G06F18/2431 , G06V40/16
CPC classification number: G06V40/172 , G06F18/2113 , G06F18/217 , G06F18/22 , G06F18/2431
Abstract: A method is provided for evaluating an effect of classifying a fuzzy attribute of an object, the fuzzy attribute referring to an attribute, a boundary between two similar ones of a plurality of categories of which is blurred, wherein the method includes: generating a similarity-based ranked confusion matrix, which comprises: based on similarities of K categories of the fuzzy attribute of the object, ranking the K categories, where K is an integer greater than or equal to 2, generating a K×K all-zero initialization matrix, wherein an abscissa and an ordinate of the initialization matrix respectively represent predicted values and true values of the similarity-based ranked categories of the fuzzy attribute, and based on the true values and the predicted values of the category of the fuzzy attribute for the multiple object samples, updating values of corresponding elements in the initialization matrix; and displaying the similarity-based ranked confusion matrix.
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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
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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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
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.
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公开(公告)号：US11954828B2
公开(公告)日：2024-04-09
申请号：US17501990
申请日：2021-10-14
Applicant: Lemon Inc.
Inventor： Jing Liu , Chunpong Lai , Guoxian Song , Linjie Luo , Ye Yuan
CPC classification number: G06T5/005 , G06T3/40 , G06T5/50 , G06T7/11 , G06T11/001 , G06T2207/10024 , G06T2207/20084 , G06T2207/20221 , G06T2207/30201
Abstract: Systems and method directed to generating a stylized image are disclosed. In particular, the method includes, in a first data path, (a) applying first stylization to an input image and (b) applying enlargement to the stylized image from (a). The method also includes, in a second data path, (c) applying segmentation to the input image to identify a face region of the input image and generate a mask image, and (d) applying second stylization to an entirety of the input image and inpainting to the identified face region of the stylized image. Machine-assisted blending is performed based on (1) the stylized image after the enlargement from the first data path, (2) the inpainted image from the second data path, and (3) the mask image, in order to obtain a final stylized image.
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