Systems and methods for reconstructing frames

Number: 10972749
Published: 2021-04-06
Filed: 2019-08-29
Assignee: Disney Enterprises, Inc.
Inventors: Schroers; Christopher, Campos; Joaquim, Djelouah; Abdelaziz, Xue; Yuanyi, Doggett; Erika Varis, McPhillen; Jared, Labrozzi; Scott
CPC: H04N19/20; G06V20/46; G06V10/462; H04N19/182; H04N19/172; G06V10/62; G06F18/214; G06V10/82; H04N19/597; G06V10/70; G06T7/254; G06F18/21; H04N19/573
Verdict: Set aside video frame reconstruction, codec-adjacent, no creative hook
Source: Google Patents · FreePatentsOnline

Abstract

Systems and methods are disclosed for reconstructing a frame. A computer-implemented method may use a computer system that includes non-transient electronic storage, a graphical user interface, and one or more physical computer processors. The computer-implemented method may include: obtaining one or more reference frames from non-transient electronic storage, generating one or more displacement maps based on the one or more reference frames and a target frame with the physical computer processor, generating one or more warped frames based on the one or more reference frames and the one or more displacement maps with the physical computer processor, obtaining a conditioned reconstruction model from the non-transient electronic storage, and generating one or more blending coefficients and one or more reconstructed displacement maps by applying the one or more displacement maps, the one or more warped frames, and a target frame to the conditioned reconstruction model with the physical computer processor.

Background

TECHNICAL FIELD (1) The present disclosure relates generally to encoders and decoders. BRIEF SUMMARY OF THE DISCLOSURE (2) Embodiments of the disclosure are directed to systems and methods for reconstructing a frame. In one embodiment, a computer-implemented method may include obtaining one or more reference frames from non-transient electronic storage. The computer-implemented method may include generating, with an optical flow model, one or more displacement maps based on the one or more reference frames and a target frame with the physical computer processor. The computer-implemented method may also include obtaining a conditioned reconstruction model from the non-transient electronic storage. The conditioned reconstruction model is conditioned by training an initial reconstruction model using training content. The training content may include a training target frame and one or more training reference frames. The computer-implemented method may further include generating one or more blending coefficients and one or more reconstructed displacement maps by applying the one or more displacement maps, the one or more warped frames, and a target frame to the conditioned reconstruction model with the physical computer processor. (3) In embodiments, the computer-implemented method may include obtaining one or more reconstructed reference frames from the non-transient electronic storage. The computer-implemented method may also include generating a reconstructed target frame using

Claims

1. A computer-implemented method comprising: generating, using an optical flow model, one or more displacement maps based on one or more reference frames and a target frame; generating one or more warped frames based on the one or more reference frames and the one or more displacement maps; generating a conditioned reconstruction model by training an initial reconstruction model using training content and one or more reconstruction parameters, wherein the training content comprising a training target frame and one or more training reference frames, and wherein the conditioned reconstruction model optimizes for the one or more reconstruction parameters; and generating, using the conditioned reconstruction model, one or more blending coefficients and one or more reconstructed displacement maps based on the one or more displacement maps, the one or more warped frames, and the target frame. || 9. A computer-implemented method comprising: obtaining training content, wherein the training content comprises a training target frame and one or more training reference frames, wherein the training target frame and the one or more training reference frames are used to generate one or more corresponding training displacement maps and one or more corresponding training warped frames; and generating a conditioned reconstruction model by training an initial reconstruction model using the training content and one or more reconstruction parameters, wherein the conditioned reconstruction model optimizes for the one or more reconstruction parameters. || 14. 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: generating a conditioned reconstruction model by training an initial reconstruction model using training content and one or more reconstruction parameters, the training content comprising a training target frame and one or more target reference frames, wherein the conditioned reconstruction model optimizes for the one or more reconstruction parameters; and generating, using the conditioned reconstruction model, one or more blending coefficients and one or more reconstructed displacement maps by applying target content to the conditioned reconstruction model.