Patents by Inventor Abhishek Lalwani

Abhishek Lalwani 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: 20240221252
    Abstract: Systems and methods for image processing are described. Embodiments of the present disclosure identify an original image depicting a face, identify a scribble image including a mask that indicates a portion of the original image for adding makeup to the face, and generate a target image depicting the face using a machine learning model based on the original image and the scribble image, where the target image includes the makeup in the portion indicated by the scribble image.
    Type: Application
    Filed: January 4, 2023
    Publication date: July 4, 2024
    Inventors: Abhishek Lalwani, Xiaoyang Li, Yijun Li
  • Patent number: 11944903
    Abstract: In various embodiments of the present disclosure, playstyle patterns of players are learned and used to generate virtual representations (“bots”) of users. Systems and methods are disclosed that use game session data (e.g., metadata) from a plurality of game sessions of a game to learn playstyle patterns of users, based on user inputs of the user in view of variables presented within the game sessions. The game session data is applied to one or more machine learning models to learn playstyle patterns of the user for the game, and associated with a user profile of the user. Profile data representative of the user profile is then used to control or instantiate bots of the users, or of categories of users, according to the learned playstyle patterns.
    Type: Grant
    Filed: February 25, 2021
    Date of Patent: April 2, 2024
    Assignee: NVIDIA Corporation
    Inventors: Andrew Fear, Brian Burke, Pillulta Venkata Naga Hanumath Prasad, Abhishek Lalwani
  • Publication number: 20210178269
    Abstract: In various embodiments of the present disclosure, playstyle patterns of players are learned and used to generate virtual representations (“bots”) of users. Systems and methods are disclosed that use game session data (e.g., metadata) from a plurality of game sessions of a game to learn playstyle patterns of users, based on user inputs of the user in view of variables presented within the game sessions. The game session data is applied to one or more machine learning models to learn playstyle patterns of the user for the game, and associated with a user profile of the user. Profile data representative of the user profile is then used to control or instantiate bots of the users, or of categories of users, according to the learned playstyle patterns.
    Type: Application
    Filed: February 25, 2021
    Publication date: June 17, 2021
    Inventors: Andrew Fear, Brian Burke, Pillulta Venkata Naga Hanumath Prasad, Abhishek Lalwani
  • Patent number: 10946281
    Abstract: In various embodiments of the present disclosure, playstyle patterns of players are learned and used to generate virtual representations (“bots”) of users. Systems and methods are disclosed that use game session data (e.g., metadata) from a plurality of game sessions of a game to learn playstyle patterns of users, based on user inputs of the user in view of variables presented within the game sessions. The game session data is applied to one or more machine learning models to learn playstyle patterns of the user for the game, and associated with a user profile of the user. Profile data representative of the user profile is then used to control or instantiate bots of the users, or of categories of users, according to the learned playstyle patterns.
    Type: Grant
    Filed: March 29, 2019
    Date of Patent: March 16, 2021
    Assignee: NVIDIA Corporation
    Inventors: Andrew Fear, Brian Burke, Pillulta Venkata Naga Hanumath Prasad, Abhishek Lalwani
  • Publication number: 20200306638
    Abstract: In various embodiments of the present disclosure, playstyle patterns of players are learned and used to generate virtual representations (“bots”) of users. Systems and methods are disclosed that use game session data (e.g., metadata) from a plurality of game sessions of a game to learn playstyle patterns of users, based on user inputs of the user in view of variables presented within the game sessions. The game session data is applied to one or more machine learning models to learn playstyle patterns of the user for the game, and associated with a user profile of the user. Profile data representative of the user profile is then used to control or instantiate bots of the users, or of categories of users, according to the learned playstyle patterns.
    Type: Application
    Filed: March 29, 2019
    Publication date: October 1, 2020
    Inventors: Andrew Fear, Brian Burke, Pillulta Venkata Naga Hanumath Prasad, Abhishek Lalwani