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    PARAMETER MAP FOR MACHINE-LEARNED VIDEO COMPRESSION
    5.
    发明申请
    PARAMETER MAP FOR MACHINE-LEARNED VIDEO COMPRESSION 有权

    公开(公告)号：US20220224914A1

    公开(公告)日：2022-07-14

    申请号：US17466797

    申请日：2021-09-03

    申请人： WaveOne Inc.

    发明人： Alexander G. Anderson ,  Oren Rippel ,  Kedar Tatwawadi ,  Sanjay Nair ,  Craig Lytle ,  Hervé Guihot ,  Brandon Sprague ,  Lubomir Bourdev

    IPC分类号： H04N19/149 ,  H04N19/65 ,  H04N19/172 ,  H04N19/166 ,  H04N19/114 ,  G06N3/04

    摘要： A compression system trains a machine-learned compression model that includes components for an encoder and decoder. In one embodiment, the compression model is trained to receive parameter information on how a target frame should be encoded with respect to one or more encoding parameters, and encodes the target frame according to the respective values of the encoding parameters for the target frame. In particular, the encoder of the compression model includes at least an encoding system configured to encode a target frame and generate compressed code that can be transmitted by, for example, a sender system to a receiver system. The decoder of the compression model includes a decoding system trained in conjunction with the encoding system. The decoding system is configured to receive the compressed code for the target frame and reconstruct the target frame for the receiver system.

    SYSTEM FOR TRAINING AND DEPLOYING FILTERS FOR ENCODING AND DECODING
    7.
    发明申请
    SYSTEM FOR TRAINING AND DEPLOYING FILTERS FOR ENCODING AND DECODING 有权

    公开(公告)号：US20230018461A1

    公开(公告)日：2023-01-19

    申请号：US17374826

    申请日：2021-07-13

    申请人： WaveOne Inc.

    发明人： Lubomir Bourdev ,  Alexander G. Anderson ,  Kedar Tatwawadi ,  Sanjay Nair ,  Craig Lytle ,  Hervé Guihot ,  Brandon Sprague ,  Oren Rippel

    IPC分类号： H04N19/117 ,  H04N19/42 ,  G06N3/04 ,  G06N20/00

    摘要： A cloud service system manages a filter repository including filters for encoding and decoding media content (e.g. text, image, audio, video, etc.). The cloud service system may receive a request from a client device to provide a filter for installation on a node such as an endpoint device (e.g. pipeline node). The request includes information such as a type of bitstream to be processed by the requested filter. The request may further include other information such as hardware configuration and functionality attribute. The cloud service system may access the filter repository that stores the plurality of filters including encoder filters and decoder filters and may select a filter that is configured to process the type of bitstream identified in the request and provide the selected filter to the client device.

    MACHINE-LEARNED IN-LOOP PREDICTOR FOR VIDEO COMPRESSION
    8.
    发明申请
    MACHINE-LEARNED IN-LOOP PREDICTOR FOR VIDEO COMPRESSION 有权

    公开(公告)号：US20220224934A1

    公开(公告)日：2022-07-14

    申请号：US17411385

    申请日：2021-08-25

    申请人： WaveOne Inc.

    发明人： Oren Rippel ,  Alexander G. Anderson ,  Kedar Tatwawadi ,  Sanjay Nair ,  Craig Lytle ,  Hervé Guihot ,  Brandon Sprague ,  Lubomir Bourdev

    IPC分类号： H04N19/52 ,  H04N19/105 ,  H04N19/30 ,  H04N19/176 ,  G06N3/08

    摘要： A compression system trains a compression model for an encoder and decoder. In one embodiment, the compression model includes a machine-learned in-loop flow predictor that generates a flow prediction from previously reconstructed frames. The machine-learned flow predictor is coupled to receive a set of previously reconstructed frames and output a flow prediction for a target frame that is an estimation of the flow for the target frame. In particular, since the flow prediction can be generated by the decoder using the set of previously reconstructed frames, the encoder may transmit a flow delta that indicates a difference between the flow prediction and the actual flow for the target frame, instead of transmitting the flow itself. In this manner, the encoder can transmit a significantly smaller number of bits to the receiver, improving computational efficiency.