公开(公告)号：US12277676B2

公开(公告)日：2025-04-15

申请号：US17770993

申请日：2020-11-11

Applicant: POSTECH RESEARCH AND BUSINESS DEVELOPMENT FOUNDATION

Inventor： Seung Yong Lee ,  Sung Hyun Cho ,  Hyeong Seok Son

IPC: G06K9/00 ,  G06N3/045 ,  G06N3/0455 ,  G06N3/0464 ,  G06N3/0475 ,  G06N3/08 ,  G06N3/088 ,  G06T3/4046 ,  G06T5/00 ,  G06T5/50 ,  G06T5/60 ,  G06T5/90 ,  G06V10/44 ,  G06V10/778 ,  G06V10/82 ,  G06V10/98 ,  G06N3/09

Abstract: An image processing method and apparatus based on machine learning are disclosed. The image processing method based on machine learning, according to the present invention, may comprise the steps of: generating a first corrected image by inputting an input image to a first convolution neural network; generating an intermediate image on the basis of the input image; performing machine learning on a first loss function of the first convolution neural network on the basis of the first corrected image and the intermediate image; and performing machine learning on a second loss function of the first convolution neural network on the basis of the first corrected image and a natural image.

公开(公告)号：US12175639B2

公开(公告)日：2024-12-24

申请号：US17497824

申请日：2021-10-08

Applicant: POSTECH Research and Business Development Foundation

Inventor： Seung Yong Lee ,  Jun Yong Lee ,  Hyeong Seok Son ,  Sung Hyun Cho

IPC: G06T5/73 ,  G06N3/04 ,  G06T5/50 ,  G06T7/246 ,  G06T7/33

Abstract: A video quality improvement method may comprise: inputting a structure feature map converted from current target frame by first convolution layer to first multi-task unit and second multi-task unit, which is connected to an output side of first multi-task unit, among the plurality of multi-task units; inputting a main input obtained by adding the structure feature map to a feature space, which is converted by second convolution layer from those obtained by concatenating, in channel dimension, a previous target frame and a correction frame of the previous frame to first multi-task unit; and inputting current target frame to Nth multi-task unit connected to an end of output side of second multi-task unit, wherein Nth multi-task unit outputs a correction frame of current target frame, and machine learning of the video quality improvement model is performed using an objective function calculated through the correction frame of current target frame.