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    METHOD AND APPARATUS WITH ADAPTIVE SUPER SAMPLING
    1.
    发明公开
    METHOD AND APPARATUS WITH ADAPTIVE SUPER SAMPLING 审中-公开

    公开(公告)号：US20240161236A1

    公开(公告)日：2024-05-16

    申请号：US18316120

    申请日：2023-05-11

    Applicant: SAMSUNG ELECTRONICS CO., LTD.

    Inventor： Hwiryong JUNG ,  Nahyup KANG ,  Hanjun KIM ,  Jaeyoung MOON ,  Hyeonseung YU ,  Juyoung LEE ,  Inwoo HA ,  Seokpyo HONG

    IPC: G06T3/40 ,  G06T7/246 ,  G06V10/75

    CPC classification number: G06T3/4053 ,  G06T7/248 ,  G06V10/7515

    Abstract: An adaptive super sampling method includes: rendering frames of a three-dimensional (3D) model, the frames including a current frame and a previous frame preceding the current frame; determining motion vectors indicating a correspondence relationship between pixels in the current frame and pixels in the previous frame; generating a geometric identifier maps (G-ID maps) respectively corresponding to the current frame and the previous frame based on 3D geometrical properties associated with the pixels in the current frame and the previous frame; based on the motion vectors and the G-ID maps, generating an artifact map predicting where artifacts will occur from inter-frame super sampling of the current frame; and performing adaptive super sampling on the current frame based on the artifact map.

    DEVICE AND METHOD WITH INCREASING RESOLUTION OF FRAME IN G-BUFFER DOMAIN
    3.
    发明公开
    DEVICE AND METHOD WITH INCREASING RESOLUTION OF FRAME IN G-BUFFER DOMAIN 审中-公开

    公开(公告)号：US20240249383A1

    公开(公告)日：2024-07-25

    申请号：US18351963

    申请日：2023-07-13

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： Seokpyo HONG ,  Nahyup KANG ,  Hanjun KIM ,  Jaeyoung MOON ,  Hyeonseung YU ,  Juyoung LEE ,  Hwiryong JUNG ,  Inwoo HA

    IPC: G06T3/40 ,  G06T3/00

    CPC classification number: G06T3/4053 ,  G06T3/0093 ,  G06T3/4046

    Abstract: A method includes: inserting new pixels between original pixels for each of maps included in a first geometry buffer (or G-buffer) generated from a frame, wherein the maps represent geometric information of a three-dimensional (3D) model of an object included in the frame; generating a second G-buffer by setting values of the new pixels using a motion vector map that may be one of the maps; generating a third G-buffer by combining, with the second G-buffer, a result of updating only values of pixels masked based on an output of a pixel masking neural network to which the second G-buffer may be input; generating a fourth G-buffer by updating values of pixels by inputting the third G-buffer to a G-buffer reconstruction neural network; and update, based on the fourth G-buffer, the resolution of a subsequent frame that follows the frame.

    IMAGE PROCESSING METHOD AND APPARATUS USING CONVOLUTIONAL NEURAL NETWORK
    6.
    发明公开
    IMAGE PROCESSING METHOD AND APPARATUS USING CONVOLUTIONAL NEURAL NETWORK 审中-公开

    公开(公告)号：US20230206617A1

    公开(公告)日：2023-06-29

    申请号：US18068209

    申请日：2022-12-19

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： Daehyun BAN ,  Daehun KIM ,  Yongsung KIM ,  Dongwan LEE ,  Juyoung LEE

    IPC: G06V10/82 ,  G06T5/20 ,  G06T7/50 ,  G06T7/70 ,  G06V10/764 ,  H04N19/59

    CPC classification number: G06V10/82 ,  G06T5/20 ,  G06T7/50 ,  G06T7/70 ,  G06V10/764 ,  H04N19/59

    Abstract: An apparatus is provided. The apparatus includes an input/output interface configured to receive an image and output a result, a memory storing one or more instructions for processing the image by using a convolutional neural network, and a processor configured to process the image by executing the one or more instructions, wherein the convolutional neural network (CNN) may include one or more spatial transformation modules, and the spatial transformation module may include a spatial transformer configured to apply a spatial transform to first input data that is the image or an output of a previous spatial transformation module, by using a spatial transformation function, a first convolutional layer configured to perform a convolution operation between the first input data to which the spatial transform is applied and a first filter, and a spatial inverse transformer configured to apply a spatial inverse transform to an output of the first convolutional layer.

    SERVER FOR POSE ESTIMATION AND OPERATING METHOD OF THE SERVER
    7.
    发明公开
    SERVER FOR POSE ESTIMATION AND OPERATING METHOD OF THE SERVER 审中-公开

    公开(公告)号：US20230169679A1

    公开(公告)日：2023-06-01

    申请号：US17963419

    申请日：2022-10-11

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： Yongsung KIM ,  Hyunsoo CHOI ,  Daehyun BAN ,  Dongwan LEE ,  Juyoung LEE

    IPC: G06T7/73 ,  G06T3/60

    CPC classification number: G06T7/73 ,  G06T3/60 ,  G06T2207/30196 ,  G06T2207/20081

    Abstract: A server for pose estimation of a person and an operating method of the server are provided. The operating method includes obtaining an original image including a person, generating a plurality of input images by rotating the original image, obtaining first pose estimation results respectively corresponding to the plurality of input images, by inputting the plurality of input images to a pose estimation model, applying weights to the first pose estimation results respectively corresponding to the plurality of input images, and obtaining a second pose estimation result, based on the first pose estimation results to which the weights are applied, wherein the first pose estimation results and the second pose estimation result each include data indicating main body parts of the person.

    IMAGE PROCESSING APPARATUS AND OPERATING METHOD THEREOF
    8.
    发明申请
    IMAGE PROCESSING APPARATUS AND OPERATING METHOD THEREOF 有权

    公开(公告)号：US20220375032A1

    公开(公告)日：2022-11-24

    申请号：US17745192

    申请日：2022-05-16

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： Daehyun BAN ,  Yongsung KIM ,  Dongwan LEE ,  Juyoung LEE

    IPC: G06T3/40 ,  G06V10/77 ,  G06T5/30 ,  G06T5/50

    Abstract: A method of operating an image processing apparatus is provided. The method includes generating a first feature map by performing a convolution operation between a first image and a first kernel group, generating a second feature map by performing a convolution operation between the first image and a second kernel group, generating a first combination map based on the first feature map, generating a second combination map based on the first feature map and the second feature map, generating a second image based on the first combination map and the second combination map, and generating a reconstructed image of the first image, based on the second image and the first image, and generating a high-resolution image of the first image by inputting the reconstructed image to an upscaling model.

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