Patents by Inventor Xiaowen YING

Xiaowen YING 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).

  • Publication number: 20240394893
    Abstract: Systems, methods, and computer-readable media are provided for performing image segmentation with depth filtering. In some examples, a method can include obtaining a frame capturing a scene: generating, based on the frame, a first segmentation map including a target segmentation mask identifying a target of interest and one or more background masks identifying one or more background regions of the frame; and generating a second segmentation map including the first segmentation map with the one or more background masks filtered out, the one or more background masks being filtered from the first segmentation map based on a depth map associated with the frame.
    Type: Application
    Filed: December 1, 2021
    Publication date: November 28, 2024
    Inventors: Yingyong QI, Xin LI, Xiaowen YING, Shuai ZHANG
  • Patent number: 12141981
    Abstract: Systems and techniques are provided for performing semantic image segmentation using a machine learning system (e.g., including one or more cross-attention transformer layers). For instance, a process can include generating one or more input image features for a frame of image data and generating one or more input depth features for a frame of depth data. One or more fused image features can be determined, at least in part, by fusing the one or more input depth features with the one or more input image features, using a first cross-attention transformer network. One or more segmentation masks can be generated for the frame of image data based on the one or more fused image features.
    Type: Grant
    Filed: February 10, 2022
    Date of Patent: November 12, 2024
    Assignee: QUALCOMM Incorporated
    Inventors: Shuai Zhang, Xiaowen Ying, Jiancheng Lyu, Yingyong Qi
  • Publication number: 20230306600
    Abstract: Systems and techniques are provided for performing semantic image segmentation using a machine learning system (e.g., including one or more cross-attention transformer layers). For instance, a process can include generating one or more input image features for a frame of image data and generating one or more input depth features for a frame of depth data. One or more fused image features can be determined, at least in part, by fusing the one or more input depth features with the one or more input image features, using a first cross-attention transformer network. One or more segmentation masks can be generated for the frame of image data based on the one or more fused image features.
    Type: Application
    Filed: February 10, 2022
    Publication date: September 28, 2023
    Inventors: Shuai ZHANG, Xiaowen YING, Jiancheng LYU, Yingyong QI