VIDEO CODING USING OPTICAL FLOW AND RESIDUAL PREDICTORS

    公开(公告)号:US20240015318A1

    公开(公告)日:2024-01-11

    申请号:US17862217

    申请日:2022-07-11

    CPC classification number: H04N19/52 H04N19/137 H04N19/105 H04N19/172

    Abstract: Systems and techniques are provided for coding video data based on an optical flow correction and a residual correction. For example, a decoding device can obtain a frame of encoded video data associated with an input frame, the frame of encoded video data including an optical flow correction and a residual correction. A predicted optical flow can be generated based on one or more reference frames and a reference optical flow. A corrected prediction frame can be generated based on the predicted optical flow and the optical flow correction. A predicted residual can be generated based on at least the corrected prediction frame and a first reference frame included in the one or more reference frames. The decoding device can generate a reconstructed input frame based on the corrected prediction frame, the predicted residual, and the residual correction.

    FLOW-AGNOSTIC NEURAL VIDEO COMPRESSION
    12.
    发明公开

    公开(公告)号:US20230169694A1

    公开(公告)日:2023-06-01

    申请号:US17975471

    申请日:2022-10-27

    CPC classification number: G06T9/002

    Abstract: A processor-implemented method for video compression using an artificial neural network (ANN) includes receiving a video via the ANN. The ANN extracts a first set of features of a current frame of the video and a second set of features of a reference frame of the video. The ANN determines an estimate of correlation features between the first set of features of the current frame and the second set of features of the reference frame. The estimate of the correlation features are encoded and transmitted to a receiver.

    LEARNED B-FRAME CODING USING P-FRAME CODING SYSTEM

    公开(公告)号:US20220295095A1

    公开(公告)日:2022-09-15

    申请号:US17198813

    申请日:2021-03-11

    Abstract: Techniques are described for processing video data, such as by performing learned bidirectional coding using a unidirectional coding system and an interpolated reference frame. For example, a process can include obtaining a first reference frame and a second reference frame. The process can include generating a third reference frame at least in part by performing interpolation between the first reference frame and the second reference frame. The process can include performing unidirectional inter-prediction on an input frame based on the third reference frame, such as by estimating motion between an input frame and the third reference frame, and generating a warped frame at least in part by warping one or more pixels of the third reference frame based on the estimated motion. The process can include generating, based on the warped frame and a predicted residual, a reconstructed frame representing the input frame, the reconstructed frame including a bidirectionally-predicted frame.

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