Techniques for understanding how trained neural networks operate

    公开(公告)号:US11568212B2

    公开(公告)日:2023-01-31

    申请号:US16533301

    申请日:2019-08-06

    Abstract: In various embodiments, a relevance application quantifies how a trained neural network operates. In operation, the relevance application generates a set of input distributions based on a set of input points associated with the trained neural network. Each input distribution is characterized by a mean and a variance associated with a different neuron included in the trained neural network. The relevance application propagates the set of input distributions through a probabilistic neural network to generate at least a first output distribution. The probabilistic neural network is derived from at least a portion of the trained neural network. Based on the first output distribution, the relevance application computes a contribution of a first input point included in the set of input points to a difference between a first output point associated with a first output of the trained neural network and an estimated mean prediction associated with the first output.

    Pose estimation and body tracking using an artificial neural network

    公开(公告)号:US10970849B2

    公开(公告)日:2021-04-06

    申请号:US16386173

    申请日:2019-04-16

    Abstract: According to one implementation, a pose estimation and body tracking system includes a computing platform having a hardware processor and a system memory storing a software code including a tracking module trained to track motions. The software code receives a series of images of motion by a subject, and for each image, uses the tracking module to determine locations corresponding respectively to two-dimensional (2D) skeletal landmarks of the subject based on constraints imposed by features of a hierarchical skeleton model intersecting at each 2D skeletal landmark. The software code further uses the tracking module to infer joint angles of the subject based on the locations and determine a three-dimensional (3D) pose of the subject based on the locations and the joint angles, resulting in a series of 3D poses. The software code outputs a tracking image corresponding to the motion by the subject based on the series of 3D poses.

    Video Color Propagation
    5.
    发明申请

    公开(公告)号:US20200077065A1

    公开(公告)日:2020-03-05

    申请号:US16119792

    申请日:2018-08-31

    Abstract: A video processing system includes a computing platform having a hardware processor and a memory storing a software code including a convolutional neural network (CNN). The hardware processor executes the software code to receive video data including a key video frame in color and a video sequence in gray scale, determine a first estimated colorization for each frame of the video sequence except the key video frame based on a colorization of a previous frame, and determine a second estimated colorization for each frame of the video sequence except the key video frame based on the key video frame in color. For each frame of the video sequence except the key video frame, the software code further blends the first estimated colorization with the second estimated colorization using a color fusion stage of the CNN to produce a colorized video sequence corresponding to the video sequence in gray scale.

    Methods and systems of enriching blendshape rigs with physical simulation

    公开(公告)号:US10297065B2

    公开(公告)日:2019-05-21

    申请号:US15347296

    申请日:2016-11-09

    Abstract: Methods, systems, and computer-readable memory are provided for determining time-varying anatomical and physiological tissue characteristics of an animation rig. For example, shape and material properties are defined for a plurality of sample configurations of the animation rig. The shape and material properties are associated with the plurality of sample configurations. An animation of the animation rig is obtained, and one or more configurations of the animation rig are determined for one or more frames of the animation. The determined one or more configurations include shape and material properties, and are determined using one or more sample configurations of the animation rig. A simulation of the animation rig is performed using the determined one or more configurations. Performing the simulation includes computing physical effects for addition to the animation of the animation rig.

    CREATION OF NON-LINEARLY CONNECTED TRANSMEDIA CONTENT DATA

    公开(公告)号:US20190098370A1

    公开(公告)日:2019-03-28

    申请号:US15715898

    申请日:2017-09-26

    Abstract: The invention relates to systems and methods for manipulating non-linearly connected transmedia content, in particular for creating, processing and/or managing non-linearly connected transmedia content and for tracking content creation and attributing transmedia content to one or more creators. Specifically, the invention involves creating a transmedia content data item by a first user and storing the transmedia content data item in a data store, along with a record indicating an association between the first user and the transmedia content data item; creating an ordered group of transmedia content data items by a second user, the ordered group comprising a pointer to the transmedia content data item of the first user; and storing the ordered group and a record associating both the first user and the second user with the ordered group in the data store.

    SYSTEM FOR OPTIMIZED EMBEDDING AND ANALYSIS OF BRANDED CONTENT

    公开(公告)号:US20190096094A1

    公开(公告)日:2019-03-28

    申请号:US15715935

    申请日:2017-09-26

    Abstract: The present disclosure relates to an apparatus, system and method for processing transmedia content data. More specifically, the disclosure provides for identifying and inserting one item of media content within another item of media content, e.g. inserting a video within a video, such that the first item of media content appears as part of the second item. The invention involves analysing a first visual media item to identify one or more spatial locations to insert the second visual media item within the image data of the first visual media item, detecting characteristics of the one or more identified spatial locations, transforming the second visual media item according to the detected characteristics and combining the first visual media item and second visual media item by inserting the transformed second visual media item into the first visual media item at the one or more identified spatial locations.

    Circular Visual Representation of Media Content

    公开(公告)号:US20180218520A1

    公开(公告)日:2018-08-02

    申请号:US15419679

    申请日:2017-01-30

    Abstract: According to one implementation, a system for visualizing media content includes a computing platform including a hardware processor and a system memory, storing a content visualization software code. The hardware processor is configured to execute the content visualization software code to receive a media file, parse the media file to identify a primary content and metadata describing the primary content, and analyze the metadata to determine representative features of the primary content. The hardware processor further executes the content visualization software code to generate a circular visual representation of the primary content based on the metadata and the representative features, the circular visual representation having a non-linear correspondence to at least one of the representative features. The circular visual representation includes a central circle having a central radius, and multiple, at least semicircular segments, each having a respective radius greater than the central radius.

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