Patents by Inventor Maxine Perroni-Scharf

Maxine Perroni-Scharf 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).

  • Modifying materials of three-dimensional digital scenes utilizing a visual neural network
    Patent number: 11972534
    Abstract: Methods, systems, and non-transitory computer readable storage media are disclosed for utilizing a visual neural network to replace materials in a three-dimensional scene with visually similar materials from a source dataset. Specifically, the disclosed system utilizes the visual neural network to generate source deep visual features representing source texture maps from materials in a plurality of source materials. Additionally, the disclosed system utilizes the visual neural network to generate deep visual features representing texture maps from materials in a digital scene. The disclosed system then determines source texture maps that are visually similar to the texture maps of the digital scene based on visual similarity metrics that compare the source deep visual features and the deep visual features. Additionally, the disclosed system modifies the digital scene by replacing one or more of the texture maps in the digital scene with the visually similar source texture maps.
    Type: Grant
    Filed: November 5, 2021
    Date of Patent: April 30, 2024
    Assignee: Adobe Inc.
    Inventors: Maxine Perroni-Scharf, Yannick Hold-Geoffroy, Kalyan Sunkavalli, Jonathan Eisenmann
  • MODIFYING MATERIALS OF THREE-DIMENSIONAL DIGITAL SCENES UTILIZING A VISUAL NEURAL NETWORK
    Publication number: 20230141395
    Abstract: Methods, systems, and non-transitory computer readable storage media are disclosed for utilizing a visual neural network to replace materials in a three-dimensional scene with visually similar materials from a source dataset. Specifically, the disclosed system utilizes the visual neural network to generate source deep visual features representing source texture maps from materials in a plurality of source materials. Additionally, the disclosed system utilizes the visual neural network to generate deep visual features representing texture maps from materials in a digital scene. The disclosed system then determines source texture maps that are visually similar to the texture maps of the digital scene based on visual similarity metrics that compare the source deep visual features and the deep visual features. Additionally, the disclosed system modifies the digital scene by replacing one or more of the texture maps in the digital scene with the visually similar source texture maps.
    Type: Application
    Filed: November 5, 2021
    Publication date: May 11, 2023
    Inventors: Maxine Perroni-Scharf, Yannick Hold-Geoffroy, Kalyan Sunkavalli, Jonathan Eisenmann