利索-全球专利检索

  1. Login
  2. Sign Up

Search Results

26 records (took 0.02 seconds)

    Depth prediction from dual pixel images
    2.
    发明授权
    Depth prediction from dual pixel images 有权

    公开(公告)号：US11599747B2

    公开(公告)日：2023-03-07

    申请号：US17090948

    申请日：2020-11-06

    Applicant: Google LLC

    Inventor： Yael Pritch Knaan ,  Marc Levoy ,  Neal Wadhwa ,  Rahul Garg ,  Sameer Ansari ,  Jiawen Chen

    IPC: G06K9/62

    Abstract: Apparatus and methods related to using machine learning to determine depth maps for dual pixel images of objects are provided. A computing device can receive a dual pixel image of at least a foreground object. The dual pixel image can include a plurality of dual pixels. A dual pixel of the plurality of dual pixels can include a left-side pixel and a right-side pixel that both represent light incident on a single dual pixel element used to capture the dual pixel image. The computing device can be used to train a machine learning system to determine a depth map associated with the dual pixel image. The computing device can provide the trained machine learning system.

    Deep Saliency Prior
    3.
    发明申请
    Deep Saliency Prior 有权

    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

    Inventor： Kfir Aberman ,  David Edward Jacobs ,  Kai Jochen Kohlhoff ,  Michael Rubinstein ,  Yossi Gandelsman ,  Junfeng He ,  Inbar Mosseri ,  Yael Pritch Knaan

    IPC: G06T7/194 ,  G06V40/20 ,  G06T7/11 ,  G06T3/00 ,  G06T11/00

    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.

    Estimating Depth Using a Single Camera
    4.
    发明申请
    Estimating Depth Using a Single Camera 审中-公开

    公开(公告)号：US20200242788A1

    公开(公告)日：2020-07-30

    申请号：US16652568

    申请日：2017-12-05

    Applicant: Google LLC

    Inventor： David Jacobs ,  Rahul Garg ,  Yael Pritch Knaan ,  Neal Wadhwa ,  Marc Levoy

    IPC: G06T7/50 ,  H04N5/232

    Abstract: A camera may capture an image of a scene and use the image to generate a first and a second subpixel image of the scene. The pair of subpixel images may be represented by a first set of subpixels and a second set of subpixels from the image respectively. Each pixel of the image may include two green subpixels that are respectively represented in the first and second subpixel images. The camera may determine a disparity between a portion of the scene as represented by the pair of subpixel images and may estimate a depth map of the scene that indicates a depth of the portion relative to other portions of the scene based on the disparity and a baseline distance between the two green subpixels. A new version of the image may be generated with a focus upon the portion and with the other portions of the scene blurred.

    High resolution inpainting with a machine-learned augmentation model and texture transfer
    6.
    发明授权
    High resolution inpainting with a machine-learned augmentation model and texture transfer 有权

    公开(公告)号：US12175642B2

    公开(公告)日：2024-12-24

    申请号：US17726720

    申请日：2022-04-22

    Applicant: Google LLC

    Inventor： Noritsugu Kanazawa ,  Neal Wadhwa ,  Yael Pritch Knaan

    IPC: G06T5/77 ,  G06T7/11 ,  G06T11/20

    Abstract: Systems and methods for augmenting images can utilize one or more image augmentation models and one or more texture transfer blocks. The image augmentation model can process input images and one or more segmentation masks to generate first output data. The first output data and the one or more segmentation masks can be processed with the texture transfer block to generate an augmented image. The input image can depict a scene with one or more occlusions, and the augmented image can depict the scene with the one or more occlusions replaced with predicted pixel data.

    Automatically Segmenting and Adjusting Images
    10.
    发明申请
    Automatically Segmenting and Adjusting Images 有权

    公开(公告)号：US20220230323A1

    公开(公告)日：2022-07-21

    申请号：US17617560

    申请日：2019-07-15

    Applicant: Google LLC

    Inventor： Orly Liba ,  Florian Kainz ,  Longqi Cai ,  Yael Pritch Knaan

    IPC: G06T7/11 ,  G06T5/00 ,  G06V10/764

    Abstract: A device automatically segments an image into different regions and automatically adjusts perceived exposure-levels or other characteristics associated with each of the different regions, to produce pictures that exceed expectations for the type of optics and camera equipment being used and in some cases, the pictures even resemble other high-quality photography created using professional equipment and photo editing software. A machine-learned model is trained to automatically segment an image into distinct regions. The model outputs one or more masks that define the distinct regions. The mask(s) are refined using a guided filter or other technique to ensure that edges of the mask(s) conform to edges of objects depicted in the image. By applying the mask(s) to the image, the device can individually adjust respective characteristics of each of the different regions to produce a higher-quality picture of a scene.

Patent Agency Ranking