Patents by Inventor Mina Doroudi

Mina Doroudi 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).

  • SYSTEM FOR CONTEXTUAL IMAGE EDITING
    Publication number: 20250245888
    Abstract: Systems, methods, and software are disclosed herein for a system by which a user can edit an image, such as an AI-generated image, using contextualized editing on an intelligent image canvas. In an implementation, a computing device receives an image generated by a generative artificial intelligence model in response to a prompt which includes a natural language request from a user. The computing device displays an image canvas of the image including multiple segments of the image which were identified by a segmentation model. The computing device displays a context menu of options to edit the image based on a selection of a segment of the image by the user. In an implementation, the computing device also displays a context menu of options to edit the image.
    Type: Application
    Filed: May 29, 2024
    Publication date: July 31, 2025
    Inventors: Mina DOROUDI, Stephanie Lorraine HORN, Rolly SETH, Priyanka Vikram SINHA, Brittany Elizabeth MEDEROS, Ian Dwyer CURRY, Aparna CHENNAPRAGADA, Derek Martin JOHNSON, Dachuan ZHANG
  • Systems and methods for dynamic image category determination
    Patent number: 11710312
    Abstract: Disclosed are systems and methods for dynamically determining categories for images. A computer-implemented method may include training a neural network to receive an input image and determine one or more image categories associated with the input image; obtaining a set of images associated with a user; determining, using the trained neural network, one or more image categories associated with each image included in the obtained set of images; determining one or more dominant image categories associated with the user based on the determined image categories for the obtained set of images; and determining an image editing user interface for the user based on the determined one or more dominant image categories.
    Type: Grant
    Filed: July 14, 2022
    Date of Patent: July 25, 2023
    Assignee: Adobe Inc.
    Inventors: Jayant Kumar, Vera Lychagina, Tarun Vashisth, Sudhakar Pandey, Sharad Mangalick, Rohith Mohan Dodle, Peter Baust, Mina Doroudi, Kerem Turgutlu, Kannan Iyer, Gaurav Kukal, Archit Kalra, Amine Ben Khalifa
  • Automatically merging people and objects from multiple digital images to generate a composite digital image
    Patent number: 11574392
    Abstract: The present disclosure relates to an image merging system that automatically and seamlessly detects and merges missing people for a set of digital images into a composite group photo. For instance, the image merging system utilizes a number of models and operations to automatically analyze multiple digital images to identify a missing person from a base image, segment the missing person from the second image, and generate a composite group photo by merging the segmented image of the missing person into the base image. In this manner, the image merging system automatically creates merged group photos that appear natural and realistic.
    Type: Grant
    Filed: February 27, 2020
    Date of Patent: February 7, 2023
    Assignee: Adobe Inc.
    Inventors: Zhe Lin, Vipul Dalal, Vera Lychagina, Shabnam Ghadar, Saeid Motiian, Rohith mohan Dodle, Prethebha Chandrasegaran, Mina Doroudi, Midhun Harikumar, Kannan Iyer, Jayant Kumar, Gaurav Kukal, Daniel Miranda, Charles R McKinney, Archit Kalra
  • Systems and Methods for Dynamic Image Category Determination
    Publication number: 20220351513
    Abstract: Disclosed are systems and methods for dynamically determining categories for images. A computer-implemented method may include training a neural network to receive an input image and determine one or more image categories associated with the input image; obtaining a set of images associated with a user; determining, using the trained neural network, one or more image categories associated with each image included in the obtained set of images; determining one or more dominant image categories associated with the user based on the determined image categories for the obtained set of images; and determining an image editing user interface for the user based on the determined one or more dominant image categories.
    Type: Application
    Filed: July 14, 2022
    Publication date: November 3, 2022
    Applicant: Adobe Inc.
    Inventors: Jayant Kumar, Vera Lychagina, Tarun Vashisth, Sudhakar Pandey, Sharad Mangalick, Rohith Mohan Dodle, Peter Baust, Mina Doroudi, Kerem Turgutlu, Kannan Iyer, Gaurav Kukal, Archit Kalra, Amine Ben Khalifa
  • Systems and methods for dynamic image category determination
    Patent number: 11468674
    Abstract: Disclosed are systems and methods for dynamically determining categories for images. A computer-implemented method includes training a neural network to receive an input image and determine one or more image categories associated with the input image; obtaining a set of images associated with a user; and determining, using the trained neural network, one or more image categories associated with each image included in the obtained set of images.
    Type: Grant
    Filed: August 18, 2020
    Date of Patent: October 11, 2022
    Assignee: Adobe Inc.
    Inventors: Jayant Kumar, Vera Lychagina, Tarun Vashisth, Sudhakar Pandey, Sharad Mangalick, Rohith Mohan Dodle, Peter Baust, Mina Doroudi, Kerem Turgutlu, Kannan Iyer, Gaurav Kukal, Archit Kalra, Amine Ben Khalifa
  • SYSTEMS AND METHODS FOR DYNAMIC IMAGE CATEGORY DETERMINATION
    Publication number: 20220058391
    Abstract: Disclosed are systems and methods for dynamically determining categories for images. A computer-implemented method includes training a neural network to receive an input image and determine one or more image categories associated with the input image; obtaining a set of images associated with a user; and determining, using the trained neural network, one or more image categories associated with each image included in the obtained set of images.
    Type: Application
    Filed: August 18, 2020
    Publication date: February 24, 2022
    Inventors: Jayant KUMAR, Vera LYCHAGINA, Tarun VASHISTH, Sudhakar PANDEY, Sharad MANGALICK, Rohith Mohan DODLE, Peter BAUST, Mina DOROUDI, Kerem TURGUTLU, Kannan IYER, Gaurav KUKAL, Archit KALRA, Amine Ben KHALIFA
  • AUTOMATICALLY MERGING PEOPLE AND OBJECTS FROM MULTIPLE DIGITAL IMAGES TO GENERATE A COMPOSITE DIGITAL IMAGE
    Publication number: 20210272253
    Abstract: The present disclosure relates to an image merging system that automatically and seamlessly detects and merges missing people for a set of digital images into a composite group photo. For instance, the image merging system utilizes a number of models and operations to automatically analyze multiple digital images to identify a missing person from a base image, segment the missing person from the second image, and generate a composite group photo by merging the segmented image of the missing person into the base image. In this manner, the image merging system automatically creates merged group photos that appear natural and realistic.
    Type: Application
    Filed: February 27, 2020
    Publication date: September 2, 2021
    Inventors: Zhe Lin, Vipul Dalal, Vera Lychagina, Shabnam Ghadar, Saeid Motiian, Rohith mohan Dodle, Prethebha Chandrasegaran, Mina Doroudi, Midhun Harikumar, Kannan Iyer, Jayant Kumar, Gaurav Kukal, Daniel Miranda, Charles R. McKinney, Archit Kalra