AUDIO-VISUAL SPEECH SEPARATION
    3.
    发明申请

    公开(公告)号:US20230122905A1

    公开(公告)日:2023-04-20

    申请号:US17951002

    申请日:2022-09-22

    Applicant: Google LLC

    Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for audio-visual speech separation. A method includes: obtaining, for each frame in a stream of frames from a video in which faces of one or more speakers have been detected, a respective per-frame face embedding of the face of each speaker; processing, for each speaker, the per-frame face embeddings of the face of the speaker to generate visual features for the face of the speaker; obtaining a spectrogram of an audio soundtrack for the video; processing the spectrogram to generate an audio embedding for the audio soundtrack; combining the visual features for the one or more speakers and the audio embedding for the audio soundtrack to generate an audio-visual embedding for the video; determining a respective spectrogram mask for each of the one or more speakers; and determining a respective isolated speech spectrogram for each speaker.

    Generating cartoon images from photos

    公开(公告)号:US10529115B2

    公开(公告)日:2020-01-07

    申请号:US15921207

    申请日:2018-03-14

    Applicant: Google LLC

    Abstract: A system and method for generating cartoon images from photos are described. The method includes receiving an image of a user, determining a template for a cartoon avatar, determining an attribute needed for the template, processing the image with a classifier trained for classifying the attribute included in the image, determining a label generated by the classifier for the attribute, determining a cartoon asset for the attribute based on the label, and rendering the cartoon avatar personifying the user using the cartoon asset.

    Text-Based Real Image Editing with Diffusion Models

    公开(公告)号:US20240355017A1

    公开(公告)日:2024-10-24

    申请号:US18302508

    申请日:2023-04-18

    Applicant: Google LLC

    CPC classification number: G06T11/60 G06T3/4053

    Abstract: Methods and systems for editing an image are disclosed herein. The method includes receiving an input image and a target text, the target text indicating a desired edit for the input image and obtaining, by the computing system, a target text embedding based on the target text. The method also includes obtaining, by the computing system, an optimized text embedding based on the target text embedding and the input image and fine-tuning, by the computing system, a diffusion model based on the optimized text embedding. The method can further include interpolating, by the computing system, the target text embedding and the optimized text embedding to obtain an interpolated embedding and generating, by the computing system, an edited image including the desired edit using the diffusion model based on the input image and the interpolated embedding.

    Deep Saliency Prior
    7.
    发明申请

    公开(公告)号:US20230015117A1

    公开(公告)日:2023-01-19

    申请号:US17856370

    申请日:2022-07-01

    Applicant: Google LLC

    Abstract: Techniques for tuning an image editing operator for reducing a distractor in raw image data are presented herein. The image editing operator can access the raw image data and a mask. The mask can indicate a region of interest associated with the raw image data. The image editing operator can process the raw image data and the mask to generate processed image data. Additionally, a trained saliency model can process at least the processed image data within the region of interest to generate a saliency map that provides saliency values. Moreover, a saliency loss function can compare the saliency values provided by the saliency map for the processed image data within the region of interest to one or more target saliency values. Subsequently, the one or more parameter values of the image editing operator can be modified based at least in part on the saliency loss function.

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