Patents by Inventor Yingcong Chen

Yingcong Chen 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).

  • Patent number: 12327328
    Abstract: Methods and systems are provided for generating enhanced image. A neural network system is trained where the training includes training a first neural network that generates enhanced images conditioned on content of an image undergoing enhancement and training a second neural network that designates realism of the enhanced images generated by the first neural network. The neural network system is trained by determine loss and accordingly adjusting the appropriate neural network(s). The trained neural network system is used to generate an enhanced aesthetic image from a selected image where the output enhanced aesthetic image has increased aesthetics when compared to the selected image.
    Type: Grant
    Filed: July 19, 2021
    Date of Patent: June 10, 2025
    Assignee: Adobe Inc.
    Inventors: Xiaohui Shen, Zhe Lin, Xin Lu, Sarah Aye Kong, I-Ming Pao, Yingcong Chen
  • Publication number: 20210350504
    Abstract: Methods and systems are provided for generating enhanced image. A neural network system is trained where the training includes training a first neural network that generates enhanced images conditioned on content of an image undergoing enhancement and training a second neural network that designates realism of the enhanced images generated by the first neural network. The neural network system is trained by determine loss and accordingly adjusting the appropriate neural network(s). The trained neural network system is used to generate an enhanced aesthetic image from a selected image where the output enhanced aesthetic image has increased aesthetics when compared to the selected image.
    Type: Application
    Filed: July 19, 2021
    Publication date: November 11, 2021
    Inventors: Xiaohui Shen, Zhe Lin, Xin Lu, Sarah Aye Kong, I-Ming Pao, Yingcong Chen
  • Patent number: 11069030
    Abstract: Methods and systems are provided for generating enhanced image. A neural network system is trained where the training includes training a first neural network that generates enhanced images conditioned on content of an image undergoing enhancement and training a second neural network that designates realism of the enhanced images generated by the first neural network. The neural network system is trained by determine loss and accordingly adjusting the appropriate neural network(s). The trained neural network system is used to generate an enhanced aesthetic image from a selected image where the output enhanced aesthetic image has increased aesthetics when compared to the selected image.
    Type: Grant
    Filed: March 22, 2018
    Date of Patent: July 20, 2021
    Assignee: Adobe, Inc.
    Inventors: Xiaohui Shen, Zhe Lin, Xin Lu, Sarah Aye Kong, I-Ming Pao, Yingcong Chen
  • Publication number: 20190295223
    Abstract: Methods and systems are provided for generating enhanced image. A neural network system is trained where the training includes training a first neural network that generates enhanced images conditioned on content of an image undergoing enhancement and training a second neural network that designates realism of the enhanced images generated by the first neural network. The neural network system is trained by determine loss and accordingly adjusting the appropriate neural network(s). The trained neural network system is used to generate an enhanced aesthetic image from a selected image where the output enhanced aesthetic image has increased aesthetics when compared to the selected image.
    Type: Application
    Filed: March 22, 2018
    Publication date: September 26, 2019
    Inventors: Xiaohui Shen, Zhe Lin, Xin Lu, Sarah Aye Kong, I-Ming Pao, Yingcong Chen