ENHANCED USER EXPERIENCE THROUGH BI-DIRECTIONAL AUDIO AND VISUAL SIGNAL GENERATION

    公开(公告)号:WO2022231762A1

    公开(公告)日:2022-11-03

    申请号:PCT/US2022/023206

    申请日:2022-04-03

    Abstract: Training a neural network for creating an output signal of different modality from an input signal is described. A first modality is a sound signal or a visual image and where the output signal is a visual image or a sound signal, respectively. In embodiments a model is trained using a pair of visual and audio networks to train a set of codebooks using known visual and audio signals and using a second pair of visual and audio networks to further train the set of codebooks using the augmented visual signals and the augmented audio signals. The visual and audio networks may be equally weighted, respectively. In aspects of the present disclosure, the set of codebooks comprise a visual codebook, an audio codebook and a correlation codebook, which are then used to create a visual image from a sound signal and/or a sound signal from a visual image.

    RELIGHTING SYSTEM FOR SINGLE IMAGES
    3.
    发明申请

    公开(公告)号:WO2022187013A1

    公开(公告)日:2022-09-09

    申请号:PCT/US2022/017181

    申请日:2022-02-22

    Abstract: In various embodiments, a computer-implemented method of training a neural network for relighting an image is described. A first training set that includes source images and a target illumination embedding is generated, the source images having respective illuminated subjects. A second training set that includes augmented images and the target illumination embedding is generated, where the augmented images corresponding to the source images. A first autoencoder is trained using the first training set to generate a first output set that includes estimated source illumination embeddings and first reconstructed images that correspond to the source images, the reconstructed images having respective subjects that are i) from the corresponding source image, and ii) illuminated based on the target illumination embedding. A second autoencoder is trained using the second training set to generate a second output set that includes estimated augmented illumination embeddings and second reconstructed images that correspond to the augmented images.

    EYE GAZE ADJUSTMENT
    4.
    发明申请
    EYE GAZE ADJUSTMENT 审中-公开

    公开(公告)号:WO2022093382A1

    公开(公告)日:2022-05-05

    申请号:PCT/US2021/048306

    申请日:2021-08-31

    Abstract: A computing system, a method, and a computer-readable storage medium for adjusting eye gaze are described. The method includes capturing a video stream including images of a user, detecting the user's face region within the images, and detecting the user's facial feature regions within the images based on the detected face region. The method includes determining whether the user is completely disengaged from the computing system and, if the user is not completely disengaged, detecting the user's eye region within the images based on the detected facial feature regions. The method also includes computing the user's desired eye gaze direction based on the detected eye region, generating gaze- adjusted images based on the desired eye gaze direction, wherein the gaze-adjusted images include a saccadic eye movement, a micro-saccadic eye movement, and/or a vergence eye movement, and replacing the images within the video stream with the gaze-adjusted images.

    CONTROLLING A FUNCTION VIA GAZE DETECTION
    5.
    发明申请

    公开(公告)号:WO2022154912A1

    公开(公告)日:2022-07-21

    申请号:PCT/US2021/062718

    申请日:2021-12-10

    Abstract: Aspects of the present disclosure relate to systems and methods for controlling a function of a computing system using gaze detection. In examples, one or more images of a user are received and gaze information may be determined from the received one or more images. Non-gaze information may be received when the gaze information is determined to satisfy a condition. Accordingly, a function may be enabled based on the received non-gaze information. In examples, the gaze information may be determined by extracting a plurality of features from the received one or more images, providing the plurality of features to a neural network, and determining, utilizing the neural network, a location at a display device at which a gaze of the user is directed.

    GAZE ADJUSTMENT AND ENHANCEMENT FOR EYE IMAGES

    公开(公告)号:WO2021066907A1

    公开(公告)日:2021-04-08

    申请号:PCT/US2020/038576

    申请日:2020-06-19

    Abstract: A method for image enhancement on a computing device includes receiving a digital input image depicting a human eye. From the digital input image, the computing device generates a gaze-adjusted image via a gaze adjustment machine learning model by changing an apparent gaze direction of the human eye. From the gaze-adjusted image and potentially in conjunction with the digital input image, the computing device generates a detail-enhanced image via a detail enhancement machine learning model by adding or modifying details. The computing device outputs the detail-enhanced image.

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