Patents by Inventor Sebastian Karol DZIADZIO

Sebastian Karol DZIADZIO 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: 20230360309
    Abstract: In various examples there is a method of image processing comprising: storing a real image of an object in memory, the object being a specified type of object. The method involves computing, using a first encoder, a factorized embedding of the real image. The method receives a value of at least one parameter of a synthetic image rendering apparatus for rendering synthetic images of objects of the specified type. The parameter controls an attribute of synthetic images of objects rendered by the rendering apparatus. The method computes an embedding factor of the received value using a second encoder. The factorized embedding is modified with the computed embedding factor. The method computes, using a decoder with the modified embedding as input, an output image of an object which is substantially the same as the real image except for the attribute controlled by the parameter.
    Type: Application
    Filed: July 18, 2023
    Publication date: November 9, 2023
    Inventors: Marek Adam KOWALSKI, Stephan Joachim GARBIN, Matthew Alastair JOHNSON, Tadas BALTRUSAITIS, Martin DE LA GORCE, Virginia ESTELLERS CASAS, Sebastian Karol DZIADZIO
  • Patent number: 11748932
    Abstract: In various examples there is a method of image processing comprising: storing a real image of an object in memory, the object being a specified type of object. The method involves computing, using a first encoder, a factorized embedding of the real image. The method receives a value of at least one parameter of a synthetic image rendering apparatus for rendering synthetic images of objects of the specified type. The parameter controls an attribute of synthetic images of objects rendered by the rendering apparatus. The method computes an embedding factor of the received value using a second encoder. The factorized embedding is modified with the computed embedding factor. The method computes, using a decoder with the modified embedding as input, an output image of an object which is substantially the same as the real image except for the attribute controlled by the parameter.
    Type: Grant
    Filed: June 29, 2020
    Date of Patent: September 5, 2023
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Marek Adam Kowalski, Stephan Joachim Garbin, Matthew Alastair Johnson, Tadas Baltrusaitis, Martin De la Gorce, Virginia Estellers Casas, Sebastian Karol Dziadzio
  • Publication number: 20220284655
    Abstract: There is a region of interest of a synthetic image depicting an object from a class of objects. A trained neural image generator, having been trained to map embeddings from a latent space to photorealistic images of objects in the class, is accessed. A first embedding is computed from the latent space, the first embedding corresponding to an image which is similar to the region of interest while maintaining photorealistic appearance. A second embedding is computed from the latent space, the second embedding corresponding to an image which matches the synthetic image. Blending of the first embedding and the second embedding is done to form a blended embedding. At least one output image is generated from the blended embedding, the output image being more photorealistic than the synthetic image.
    Type: Application
    Filed: May 23, 2022
    Publication date: September 8, 2022
    Inventors: Stephan Joachim GARBIN, Marek Adam KOWALSKI, Matthew Alastair JOHNSON, Tadas BALTRUSAITIS, Martin DE LA GORCE, Virginia ESTELLERS CASAS, Sebastian Karol DZIADZIO, Jamie Daniel Joseph SHOTTON
  • Patent number: 11354846
    Abstract: There is a region of interest of a synthetic image depicting an object from a class of objects. A trained neural image generator, having been trained to map embeddings from a latent space to photorealistic images of objects in the class, is accessed. A first embedding is computed from the latent space, the first embedding corresponding to an image which is similar to the region of interest while maintaining photorealistic appearance. A second embedding is computed from the latent space, the second embedding corresponding to an image which matches the synthetic image. Blending of the first embedding and the second embedding is done to form a blended embedding. At least one output image is generated from the blended embedding, the output image being more photorealistic than the synthetic image.
    Type: Grant
    Filed: June 29, 2020
    Date of Patent: June 7, 2022
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Stephan Joachim Garbin, Marek Adam Kowalski, Matthew Alastair Johnson, Tadas Baltrusaitis, Martin De La Gorce, Virginia Estellers Casas, Sebastian Karol Dziadzio, Jamie Daniel Joseph Shotton
  • Publication number: 20210343063
    Abstract: There is a region of interest of a synthetic image depicting an object from a class of objects. A trained neural image generator, having been trained to map embeddings from a latent space to photorealistic images of objects in the class, is accessed. A first embedding is computed from the latent space, the first embedding corresponding to an image which is similar to the region of interest while maintaining photorealistic appearance. A second embedding is computed from the latent space, the second embedding corresponding to an image which matches the synthetic image. Blending of the first embedding and the second embedding is done to form a blended embedding. At least one output image is generated from the blended embedding, the output image being more photorealistic than the synthetic image.
    Type: Application
    Filed: June 29, 2020
    Publication date: November 4, 2021
    Inventors: Stephan Joachim GARBIN, Marek Adam KOWALSKI, Matthew Alastair JOHNSON, Tadas BALTRUSAITIS, Martin DE LA GORCE, Virginia ESTELLERS CASAS, Sebastian Karol DZIADZIO, Jamie Daniel Joseph SHOTTON
  • Publication number: 20210335029
    Abstract: In various examples there is a method of image processing comprising: storing a real image of an object in memory, the object being a specified type of object. The method involves computing, using a first encoder, a factorized embedding of the real image. The method receives a value of at least one parameter of a synthetic image rendering apparatus for rendering synthetic images of objects of the specified type. The parameter controls an attribute of synthetic images of objects rendered by the rendering apparatus. The method computes an embedding factor of the received value using a second encoder. The factorized embedding is modified with the computed embedding factor. The method computes, using a decoder with the modified embedding as input, an output image of an object which is substantially the same as the real image except for the attribute controlled by the parameter.
    Type: Application
    Filed: June 29, 2020
    Publication date: October 28, 2021
    Inventors: Marek Adam KOWALSKI, Stephan Joachim GARBIN, Matthew Alastair JOHNSON, Tadas BALTRUSAITIS, Martin DE LA GORCE, Virginia ESTELLERS CASAS, Sebastian Karol DZIADZIO