Patents by Inventor Adrian-Stefan Ungureanu

Adrian-Stefan Ungureanu 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: 20250131604
    Abstract: Embodiments include obtaining a prompt and a diversity input indicating a level of adherence to the prompt. The diversity input may be implemented as a graphical user interface (GUI) element, such as a slider or field. Embodiments then generate a guidance embedding based on the prompt and the diversity input. Embodiments update the guidance embedding based on the diversity input. Subsequently, embodiments generate a synthetic image based on the guidance embedding, wherein the synthetic image depicts an element of the prompt based on the level of adherence from the diversity input.
    Type: Application
    Filed: October 20, 2023
    Publication date: April 24, 2025
    Inventors: Adrian-Stefan Ungureanu, Vlad-Constantin Lungu-Stan, Ionut Mironicã
  • Publication number: 20250095226
    Abstract: A method, apparatus, non-transitory computer readable medium, and system for generating images with an adjustable level of complexity includes obtaining a content prompt, a style prompt, and a complexity value. The content prompt describes an image element, the style prompt indicates an image style, and the complexity value indicates a level of influence of the style prompt. Embodiments then generate, using an image generation model, an output image based on the content prompt, the style prompt, and the complexity value, wherein the output image includes the image element with a level of the image style based on the complexity value.
    Type: Application
    Filed: September 13, 2024
    Publication date: March 20, 2025
    Inventors: Adrian-Stefan Ungureanu-Contes, Marian Lupascu, Vlad-Constantin Lungu-Stan, Ionut Mironicä, Vineet Batra
  • Publication number: 20250095227
    Abstract: A method, apparatus, non-transitory computer readable medium, and system for training a text-guided vector image synthesis include obtaining training data including a vectorizable image and a caption describing the vectorizable image and generating, using an image generation model, a predicted image with a first level of high frequency detail. Then, the training data and the predicted image are used to tune the image generation model to generate a synthetic vectorizable image based on the caption, where the synthetic vectorizable image has a second level of high frequency detail that is lower than the first level of high frequency detail of the predicted image.
    Type: Application
    Filed: September 16, 2024
    Publication date: March 20, 2025
    Inventors: Adrian-Stefan Ungureanu-Contes, Marian Lupascu, Vlad-Constantin Lungu-Stan, Ionuţ Mironica, Vineet Batra
  • Publication number: 20240386707
    Abstract: In implementations of systems for evaluating bias in generative models, a computing device implements a bias system to generate a modified digital image by processing an input digital image using a first machine learning model trained on training data to generate modified digital images based on input digital images. The bias system computes a first latent representation of the input digital image and a second latent representation of the modified digital image using a second machine learning model trained on training data to compute latent representations of digital images. A bias score is determined for a visual attribute based on the first latent representation and the second latent representation. The bias system generates an indication of the bias score for the visual attribute for display in a user interface.
    Type: Application
    Filed: May 18, 2023
    Publication date: November 21, 2024
    Applicant: Adobe Inc.
    Inventors: Adrian-Stefan Ungureanu, Marian Lupascu, Ionut Mironicá
  • Patent number: 12118647
    Abstract: This disclosure describes methods, non-transitory computer readable storage media, and systems that utilize one or more stages of a two-stage image colorization neural network to colorize or re-colorize digital images. In one or more embodiments, the disclosed system generates a color digital image from a grayscale digital image by utilizing a colorization neural network. Additionally, the disclosed system receives one or more inputs indicating local hints comprising one or more color selections to apply to one or more objects of the color digital image. The disclosed system then utilizes a re-colorization neural network to generate a modified digital image from the color digital image by modifying one or more colors of the object(s) based on the luminance channel, color channels, and selected color(s).
    Type: Grant
    Filed: August 18, 2021
    Date of Patent: October 15, 2024
    Assignee: Adobe Inc.
    Inventors: Adrian-Stefan Ungureanu, Ionut Mironica, Richard Zhang
  • Publication number: 20230055204
    Abstract: This disclosure describes methods, non-transitory computer readable storage media, and systems that utilize one or more stages of a two-stage image colorization neural network to colorize or re-colorize digital images. In one or more embodiments, the disclosed system generates a color digital image from a grayscale digital image by utilizing a colorization neural network. Additionally, the disclosed system receives one or more inputs indicating local hints comprising one or more color selections to apply to one or more objects of the color digital image. The disclosed system then utilizes a re-colorization neural network to generate a modified digital image from the color digital image by modifying one or more colors of the object(s) based on the luminance channel, color channels, and selected color(s).
    Type: Application
    Filed: August 18, 2021
    Publication date: February 23, 2023
    Inventors: Adrian-Stefan Ungureanu, Ionut Mironica, Richard Zhang