-
公开(公告)号：US11335034B2
公开(公告)日：2022-05-17
申请号：US16249861
申请日：2019-01-16
Applicant: Disney Enterprises, Inc.
Inventor： Christopher Schroers , Erika Doggett , Stephan Marcel Mandt , Jared McPhillen , Scott Labrozzi , Romann Weber , Mauro Bamert
Abstract: Systems and methods for predicting a target set of pixels are disclosed. In one embodiment, a method may include obtaining target content. The target content may include a target set of pixels to be predicted. The method may also include convolving the target set of pixels to generate an estimated set of pixels. The method may include matching a second set of pixels in the target content to the target set of pixels. The second set of pixels may be within a distance from the target set of pixels. The method may include refining the estimated set of pixels to generate a refined set of pixels using a second set of pixels in the target content.
-
公开(公告)号：US20190333190A1
公开(公告)日：2019-10-31
申请号：US16167388
申请日：2018-10-22
Applicant: Disney Enterprises, Inc.
Inventor： Christopher Schroers , Mauro Bamert , Erika Doggett , Jared McPhillen , Scott Labrozzi , Romann Weber
Abstract: Systems and methods for distortion removal at multiple quality levels are disclosed. In one embodiment, a method may include receiving training content. The training content may include original content, reconstructed content, and training distortion quality levels corresponding to the reconstructed content. The reconstructed content may be derived from distorted original content. The method may also include training distortion quality levels corresponding to the reconstructed content. The method may further include receiving an initial distortion removal model. The method may include generating a conditioned distortion removal model by training the initial distortion removal model using the training content. The method may further include storing the conditioned distortion removal model.
-
Patent Agency Ranking
公开(公告)号：US20200372621A1
公开(公告)日：2020-11-26
申请号：US16447768
申请日：2019-06-20
Applicant: Disney Enterprises, Inc.
Inventor： Jacek Naruniec , Romann Weber , Christopher Schroers
Abstract: An image synthesis system includes a computing platform having a hardware processor and a system memory storing a software code including a neural encoder and multiple neural decoders each corresponding to a respective persona. The hardware processor executes the software code to receive target image data, and source data that identifies one of the personas, and to map the target image data to its latent space representation using the neural encoder. The software code further identifies one of the neural decoders for decoding the latent space representation of the target image data based on the persona identified by the source data, uses the to identified neural decoder to decode the latent space representation of the target image data as the persona identified by the source data to produce a swapped image data, and blends the swapped image data with the target image data to produce one or more synthesized images.
-
公开(公告)号：US20200226797A1
公开(公告)日：2020-07-16
申请号：US16249861
申请日：2019-01-16
Applicant: Disney Enterprises, Inc.
Inventor： Christopher Schroers , Erika Doggett , Stephan Marcel Mandt , Jared McPhillen , Scott Labrozzi , Romann Weber , Mauro Bamert
IPC: G06T9/20
Abstract: Systems and methods for predicting a target set of pixels are disclosed. In one embodiment, a method may include obtaining target content. The target content may include a target set of pixels to be predicted. The method may also include convolving the target set of pixels to generate an estimated set of pixels. The method may include matching a second set of pixels in the target content to the target set of pixels. The second set of pixels may be within a distance from the target set of pixels. The method may include refining the estimated set of pixels to generate a refined set of pixels using a second set of pixels in the target content.
-
公开(公告)号：US11983906B2
公开(公告)日：2024-05-14
申请号：US17704907
申请日：2022-03-25
Applicant: DISNEY ENTERPRISES, INC.
Inventor： Christopher Schroers , Erika Doggett , Stephan Mandt , Jared Mcphillen , Scott Labrozzi , Romann Weber , Mauro Bamert
Abstract: Systems and methods for predicting a target set of pixels are disclosed. In one embodiment, a method may include obtaining target content. The target content may include a target set of pixels to be predicted. The method may also include convolving the target set of pixels to generate an estimated set of pixels. The method may include matching a second set of pixels in the target content to the target set of pixels. The second set of pixels may be within a distance from the target set of pixels. The method may include refining the estimated set of pixels to generate a refined set of pixels using a second set of pixels in the target content.
-
公开(公告)号：US10902571B2
公开(公告)日：2021-01-26
申请号：US16447768
申请日：2019-06-20
Applicant: Disney Enterprises, Inc.
Inventor： Jacek Naruniec , Romann Weber , Christopher Schroers
Abstract: An image synthesis system includes a computing platform having a hardware processor and a system memory storing a software code including a neural encoder and multiple neural decoders each corresponding to a respective persona. The hardware processor executes the software code to receive target image data, and source data that identifies one of the personas, and to map the target image data to its latent space representation using the neural encoder. The software code further identifies one of the neural decoders for decoding the latent space representation of the target image data based on the persona identified by the source data, uses the identified neural decoder to decode the latent space representation of the target image data as the persona identified by the source data to produce a swapped image data, and blends the swapped image data with the target image data to produce one or more synthesized images.
-
公开(公告)号：US10832383B2
公开(公告)日：2020-11-10
申请号：US16167388
申请日：2018-10-22
Applicant: Disney Enterprises, Inc.
Inventor： Christopher Schroers , Mauro Bamert , Erika Doggett , Jared McPhillen , Scott Labrozzi , Romann Weber
Abstract: Systems and methods for distortion removal at multiple quality levels are disclosed. In one embodiment, a method may include receiving training content. The training content may include original content, reconstructed content, and training distortion quality levels corresponding to the reconstructed content. The reconstructed content may be derived from distorted original content. The method may also include training distortion quality levels corresponding to the reconstructed content. The method may further include receiving an initial distortion removal model. The method may include generating a conditioned distortion removal model by training the initial distortion removal model using the training content. The method may further include storing the conditioned distortion removal model.
-
-
-
-
-
-
Search Results
7
records
(took 0.011 seconds)
