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    METHOD AND APPARATUS FOR MODELING OBJECT
    14.
    发明申请
    METHOD AND APPARATUS FOR MODELING OBJECT 审中-公开

    公开(公告)号：US20170098016A1

    公开(公告)日：2017-04-06

    申请号：US15241395

    申请日：2016-08-19

    Applicant: SAMSUNG ELECTRONICS CO., LTD.

    Inventor： Donghoon SAGONG ,  Nahyup KANG ,  Minjung SON ,  KeeChang LEE ,  Hyong Euk LEE ,  Heesae LEE

    IPC: G06F17/50

    Abstract: A method of modeling an object includes defining a state transition probability and a state of each of a plurality of particles forming the object; changing a state of a particle defined to be in a first state among the plurality of particles to a second state; applying a movement model to a particle defined to be in the second state among the plurality of particles; and changing a state of the particle defined to be in the second state to the first state based on the state transition probability.

    THREE-DIMENSIONAL (3D) RENDERING METHOD AND APPARATUS
    15.
    发明申请
    THREE-DIMENSIONAL (3D) RENDERING METHOD AND APPARATUS 审中-公开
    三维（3D）渲染方法和设备

    公开(公告)号：US20170032567A1

    公开(公告)日：2017-02-02

    申请号：US15076817

    申请日：2016-03-22

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： Seungin PARK ,  Minsu AHN ,  Minjung SON ,  Hyong Euk LEE ,  Inwoo HA

    IPC: G06T15/80 ,  G06T15/00 ,  G06T17/20

    CPC classification number: G06T15/80 ,  G06T15/005

    Abstract: A three-dimensional (3D) rendering method and apparatus is disclosed. The 3D rendering apparatus determines a vertex for a first shading from among vertices of a 3D model based on characteristic information of the 3D model, performs the first shading on the determined vertex, determines a pixel area for a second shading based on reference information indicating whether the first shading is applied to at least one vertex comprising the pixel area, performs the second shading on the determined pixel area, and generates a rendered image based on the first shading and the second shading.

    Abstract translation: 公开了一种三维（3D）渲染方法和装置。 3D渲染装置基于3D模型的特征信息，从3D模型的顶点确定用于第一着色的顶点，对所确定的顶点执行第一着色，基于指示是否存在第二着色的像素区域 将第一阴影应用于包括像素区域的至少一个顶点，对所确定的像素区域执行第二阴影，并且基于第一阴影和第二阴影生成渲染图像。

    RENDERING METHOD AND DEVICE
    16.
    发明申请
    RENDERING METHOD AND DEVICE 有权

    公开(公告)号：US20250078394A1

    公开(公告)日：2025-03-06

    申请号：US18666433

    申请日：2024-05-16

    Applicant: SAMSUNG ELECTRONICS CO., LTD.

    Inventor： Seokhwan JANG ,  Minjung SON ,  Sungheon PARK ,  Young Chun AHN ,  Nahyup KANG ,  Jiyeon KIM

    IPC: G06T15/20 ,  G06T3/18

    Abstract: A rendering method and rendering device are provided. The rendering method includes obtaining a target image corresponding to a target view by inputting parameter information corresponding to the target view to a neural scene representation (NSR) model, determining an adjacent view that satisfies a predetermined condition with respect to the target view, obtaining an adjacent image corresponding to the adjacent view by inputting parameter information corresponding to the adjacent view to the NSR model, and obtaining a final image by correcting the target image based on the adjacent image.

    METHOD AND APPARATUS WITH GLOBAL LOCALIZATION
    17.
    发明申请
    METHOD AND APPARATUS WITH GLOBAL LOCALIZATION 有权

    公开(公告)号：US20230114734A1

    公开(公告)日：2023-04-13

    申请号：US17699657

    申请日：2022-03-21

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： Hyewon MOON ,  Jiyeon KIM ,  Minjung SON

    IPC: G06T7/73 ,  G06N3/08

    Abstract: A method with global localization includes: extracting a feature by applying an input image to a first network; estimating a coordinate map corresponding to the input image by applying the extracted feature to a second network; and estimating a pose corresponding to the input image based on the estimated coordinate map, wherein either one or both of the first network and the second network is trained based on either one or both of: a first generative adversarial network (GAN) loss determined based on a first feature extracted by the first network based on a synthetic image determined by three-dimensional (3D) map data and a second feature extracted by the first network based on a real image; and a second GAN loss determined based on a first coordinate map estimated by the second network based on the first feature and a second coordinate map estimated by the second network based on the second feature.

    COMPUTING METHOD AND APPARATUS WITH IMAGE GENERATION
    18.
    发明申请
    COMPUTING METHOD AND APPARATUS WITH IMAGE GENERATION 有权

    公开(公告)号：US20220148127A1

    公开(公告)日：2022-05-12

    申请号：US17202899

    申请日：2021-03-16

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： Minjung SON ,  Hyun Sung CHANG

    IPC: G06T3/00 ,  G06T7/00 ,  G06T7/50 ,  G06T7/60 ,  G06N3/08

    Abstract: A method and apparatus for generating an image and for training an artificial neural network to generate an image are provided. The method of generating an image, including receiving input data comprising conditional information and image information, generating a synthesized image by applying the input data to an image generation neural network configured to maintain geometric information of the image information and to transform the remaining image information based on the conditional information, and outputting the synthesized image.

    NEURAL NETWORK RECOGNTION AND TRAINING METHOD AND APPARATUS
    19.
    发明申请
    NEURAL NETWORK RECOGNTION AND TRAINING METHOD AND APPARATUS 审中-公开

    公开(公告)号：US20190102678A1

    公开(公告)日：2019-04-04

    申请号：US15946800

    申请日：2018-04-06

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： Hyun Sung CHANG ,  Donghoon SAGONG ,  Minjung SON

    IPC: G06N3/08 ,  G06N3/04 ,  G06K9/62 ,  G06F17/18

    Abstract: Disclosed is a recognition and training method and apparatus. The apparatus may include a processor configured to input data to a neural network, determine corresponding to a multiclass output a mapping function of a first class and a mapping function of a second class, acquire a result of a loss function including a first probability component that changes correspondingly to a function value of the mapping function of the first class and a second probability component that changes contrastingly to a function value of the mapping function of the second class, determine a gradient of loss corresponding to the input data based on the result of the loss function, update a parameter of the neural network based on the determined gradient of loss for generating a trained neural network based on the updated parameter. The apparatus may input other data to the trained neural network, and indicate a recognition result.

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