Systems and methods for distortion removal at multiple quality levels

Number: 10832383
Published: 2020-11-10
Filed: 2018-10-22
Assignee: DISNEY ENTERPRISES, INC.
Inventors: Schroers; Christopher, Bamert; Mauro, Doggett; Erika, McPhillen; Jared, Labrozzi; Scott, Weber; Romann
CPC: G06N3/045; G06N3/0464; G06N3/048; G06N3/08; G06N3/09; G06T5/20; G06T5/60; G06T5/70; G06T5/80
Verdict: Set aside generic image distortion correction, no creative hook
Source: Google Patents · FreePatentsOnline

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.

Background

TECHNICAL FIELD(1) The present disclosure relates generally to distortion and artifact removal.BRIEF SUMMARY OF THE DISCLOSURE(2) Embodiments of the disclosure are directed to systems and methods trained on multiple, different training quality levels that remove distortion from media content of varying quality levels that may overlap with the multiple, different training quality levels.(3) In one embodiment, a computer-implemented method includes: receiving training content. The training content may include: original content; reconstructed content derived from distorted original content; and training distortion quality levels corresponding to the reconstructed content. The computer-implemented method may also include receiving an initial distortion removal model; generating a conditioned distortion removal model by training the initial distortion removal model using the training content; and storing the conditioned distortion removal model.(4) In embodiments, the method may further include: receiving target content. The target content may have one or more target distortion quality levels. The method may also include applying the conditioned distortion removal model to the target content to generate corrected target content.(5) In embodiments, the initial distortion removal model and the conditioned distortion removal model comprise one or more user-defined output branches based on one or more distortion quality levels.(6) The computer-implemented method of claim 3, wherein th

Claims

1. A computer-implemented method, comprising: receiving training content, the training content comprising original content and reconstructed content, wherein the reconstructed content is derived from distorted original content; generating a plurality of training distortion quality levels based on the reconstructed content; receiving an initial distortion removal model; generating a conditioned distortion removal model by training the initial distortion removal model using the training content and the plurality of training distortion quality levels; and storing the conditioned distortion removal model. 10. A computer-implemented method, comprising: receiving target content, wherein the target content has a plurality of target distortion quality levels; receiving a conditioned distortion removal model, the conditioned distortion removal model having been conditioned by training an initial distortion removal model using training content and a plurality of training distortion quality levels, wherein the training content comprises original content and reconstructed content derived from distorted original content, and wherein the plurality of training distortion quality levels are generated based on the reconstructed content; and applying the conditioned distortion removal model to the target content and the plurality of target distortion quality levels to generate corrected target content. 17. A system, comprising: a memory storing one or more instructions; and one or more processors that execute the one or more instructions to perform the steps of: obtaining target content, wherein the target content has a plurality of target distortion quality levels; obtaining a conditioned distortion removal model, the conditioned distortion removal model having been conditioned by training an initial distortion removal model using training content and a plurality of training distortion quality levels, wherein the training content comprises original content and reconstructed content derived from distorted original content, and wherein the plurality of training distortion quality levels are generated based on the reconstructed content; and applying the conditioned distortion removal model to the target content to generate corrected target content.