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    PARALLEL VIDEO PROCESSING SYSTEMS
    15.
    发明公开
    PARALLEL VIDEO PROCESSING SYSTEMS 审中-公开

    公开(公告)号：US20230186625A1

    公开(公告)日：2023-06-15

    申请号：US18108873

    申请日：2023-02-13

    Applicant: DeepMind Technologies Limited

    Inventor： Simon Osindero ,  Joao Carreira ,  Viorica Patraucean ,  Andrew Zisserman

    IPC: G06V20/40 ,  G06N3/049 ,  G06T1/20 ,  G06N3/044 ,  G06N3/045

    CPC classification number: G06V20/40 ,  G06N3/049 ,  G06T1/20 ,  G06N3/044 ,  G06N3/045 ,  G06T2200/28 ,  G06T2207/20084

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for parallel processing of video frames using neural networks. One of the methods includes receiving a video sequence comprising a respective video frame at each of a plurality of time steps; and processing the video sequence using a video processing neural network to generate a video processing output for the video sequence, wherein the video processing neural network includes a sequence of network components, wherein the network components comprise a plurality of layer blocks each comprising one or more neural network layers, wherein each component is active for a respective subset of the plurality of time steps, and wherein each layer block is configured to, at each time step at which the layer block is active, receive an input generated at a previous time step and to process the input to generate a block output.

    NEURAL NETWORK SYSTEMS FOR DECOMPOSING VIDEO DATA INTO LAYERED REPRESENTATIONS
    16.
    发明申请
    NEURAL NETWORK SYSTEMS FOR DECOMPOSING VIDEO DATA INTO LAYERED REPRESENTATIONS 有权

    公开(公告)号：US20220012898A1

    公开(公告)日：2022-01-13

    申请号：US17295321

    申请日：2019-11-20

    Applicant: DeepMind Technologies Limited

    Inventor： Joao Carreira ,  Jean-Baptiste Alayrac ,  Andrew Zisserman

    IPC: G06T7/215 ,  G06N3/04 ,  G06N3/08 ,  G06K9/62

    Abstract: A computer-implemented neural network system for decomposing input video data. A video data input receives a sequence of video image frames. The sequence is encoded, using a 3D spatio-temporal encoder neural network, into a set of latent variables representing a compressed version of the sequence. A 3D spatio-temporal decoder neural network processes the set of latent variables to generate two or more sets of decomposed video data; these may be stored, communicated, and/or made available to a user interface. Input video including undesired features such as reflections, shadows, and occlusions may thus be decomposed into two or more video sequences, one in which the undesired features are suppressed, and another containing the undesired features.

    SAMPLING LATENT VARIABLES TO GENERATE MULTIPLE SEGMENTATIONS OF AN IMAGE
    17.
    发明申请
    SAMPLING LATENT VARIABLES TO GENERATE MULTIPLE SEGMENTATIONS OF AN IMAGE 审中-公开

    公开(公告)号：US20200372654A1

    公开(公告)日：2020-11-26

    申请号：US16881775

    申请日：2020-05-22

    Applicant: DeepMind Technologies Limited

    Inventor： Simon Kohl ,  Bernardino Romera-Paredes ,  Danilo Jimenez Rezende ,  Seyed Mohammadali Eslami ,  Pushmeet Kohli ,  Andrew Zisserman ,  Olaf Ronneberger

    IPC: G06T7/10 ,  G06T7/00 ,  A61B5/00

    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a plurality of possible segmentations of an image. In one aspect, a method comprises: receiving a request to generate a plurality of possible segmentations of an image; sampling a plurality of latent variables from a latent space, wherein each latent variable is sampled from the latent space in accordance with a respective probability distribution over the latent space that is determined based on the image; generating a plurality of possible segmentations of the image, comprising, for each latent variable, processing the image and the latent variable using a segmentation neural network having a plurality of segmentation neural network parameters to generate the possible segmentation of the image; and providing the plurality of possible segmentations of the image in response to the request.

    Action recognition in videos using 3D spatio-temporal convolutional neural networks
    18.
    发明授权
    Action recognition in videos using 3D spatio-temporal convolutional neural networks 有权

    公开(公告)号：US10789479B2

    公开(公告)日：2020-09-29

    申请号：US16681671

    申请日：2019-11-12

    Applicant: DeepMind Technologies Limited

    Inventor： Joao Carreira ,  Andrew Zisserman

    IPC: G06K9/00 ,  G06K9/46 ,  G06K9/62 ,  G06N3/04 ,  G06N3/08 ,  G06T7/269

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing video data. An example system receives video data and generates optical flow data. An image sequence from the video data is provided to a first 3D spatio-temporal convolutional neural network to process the image data in at least three space-time dimensions and to provide a first convolutional neural network output. A corresponding sequence of optical flow image frames is provided to a second 3D spatio-temporal convolutional neural network to process the optical flow data in at least three space-time dimensions and to provide a second convolutional neural network output. The first and second convolutional neural network outputs are combined to provide a system output.

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