Patents by Inventor Shaofeng ZOU

Shaofeng ZOU has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Video blind denoising method based on deep learning, computer equipment and storage medium
    Patent number: 11216914
    Abstract: A video blind denoising method based on deep learning, a computer device and a computer-readable storage medium. The method includes: taking a video sequence from a video to be denoised, taking the middle frame in the video sequence as a noisy reference frame, performing an optical flow estimation on the image corresponding to the noisy reference frame and each other frame in the video sequence, to obtain optical flow fields; transforming, according to the optical flow fields, the image corresponding to each other frame in the video sequence to the noisy reference frame for registration respectively, to obtain multi-frame noisy registration images; taking the multi-frame noisy registration images as an input of a convolutional neural network, taking the noisy reference frame as the reference image, performing iterative training and denoising by using the noise2noise training principle, to obtain the denoised image. This solution may achieve the blind denoising of a video.
    Type: Grant
    Filed: April 28, 2020
    Date of Patent: January 4, 2022
    Assignees: Tsinghua Shenzhen International Graduate School, Tsinghua University
    Inventors: Xiang Xie, Shaofeng Zou, Guolin Li, Songping Mai, Zhihua Wang
  • VIDEO BLIND DENOISING METHOD BASED ON DEEP LEARNING, COMPUTER DEVICE AND COMPUTER-READABLE STORAGE MEDIUM
    Publication number: 20210327031
    Abstract: A video blind denoising method based on deep learning, a computer device and a computer-readable storage medium. The method includes: taking a video sequence from a video to be denoised, taking the middle frame in the video sequence as a noisy reference frame, performing an optical flow estimation on the image corresponding to the noisy reference frame and each other frame in the video sequence, to obtain optical flow fields; transforming, according to the optical flow fields, the image corresponding to each other frame in the video sequence to the noisy reference frame for registration respectively, to obtain multi-frame noisy registration images; taking the multi-frame noisy registration images as an input of a convolutional neural network, taking the noisy reference frame as the reference image, performing iterative training and denoising by using the noise2noise training principle, to obtain the denoised image. This solution may achieve the blind denoising of a video.
    Type: Application
    Filed: April 28, 2020
    Publication date: October 21, 2021
    Inventors: Xiang XIE, Shaofeng ZOU, Guolin LI, Songping MAI, Zhihua WANG