Patents by Inventor Jinhai SU

Jinhai SU 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).

  • Image lighting methods and apparatuses, electronic devices, and storage media
    Patent number: 11455516
    Abstract: An image lighting method includes: determining a convolutional neural network corresponding to a lighting operation type of an initial image; obtaining local feature information and global feature information of initial image according to convolutional neural network; obtaining fusion feature information of initial image according to convolutional neural network based on local feature information and global feature information; obtaining a maximum pooling result map and a minimum pooling result map according to convolutional neural network based on a luminance component map of initial image; obtaining a bilateral grid matrix of initial image based on fusion feature information, maximum pooling result map, and minimum pooling result map; and performing affine transformation on initial image according to bilateral grid matrix to obtain a target image, the target image being an image obtained after lighting initial image according to lighting operation type.
    Type: Grant
    Filed: December 26, 2019
    Date of Patent: September 27, 2022
    Assignee: SHENZHEN SENSETIME TECHNOLOGY CO., LTD.
    Inventors: Jinhai Su, Songfang Han, Qiong Yan, Haoran Wang
  • IMAGE LIGHTING METHODS AND APPARATUSES, ELECTRONIC DEVICES, AND STORAGE MEDIA
    Publication number: 20200143230
    Abstract: An image lighting method includes: determining a convolutional neural network corresponding to a lighting operation type of an initial image; obtaining local feature information and global feature information of initial image according to convolutional neural network; obtaining fusion feature information of initial image according to convolutional neural network based on local feature information and global feature information; obtaining a maximum pooling result map and a minimum pooling result map according to convolutional neural network based on a luminance component map of initial image; obtaining a bilateral grid matrix of initial image based on fusion feature information, maximum pooling result map, and minimum pooling result map; and performing affine transformation on initial image according to bilateral grid matrix to obtain a target image, the target image being an image obtained after lighting initial image according to lighting operation type.
    Type: Application
    Filed: December 26, 2019
    Publication date: May 7, 2020
    Applicant: SHENZHEN SENSETIME TECHNOLOGY CO., LTD.
    Inventors: Jinhai SU, Songfang HAN, Qiong YAN, Haoran WANG