Optimizations for dynamic object instance detection, segmentation, and structure mapping

    公开(公告)号:US10565729B2

    公开(公告)日:2020-02-18

    申请号:US15971997

    申请日:2018-05-04

    Applicant: Facebook, Inc.

    Abstract: In one embodiment, a method includes a system accessing an image and generating a feature map using a first neural network. The system identifies a plurality of regions of interest in the feature map. A plurality of regional feature maps may be generated for the plurality of regions of interest, respectively. Using a second neural network, the system may detect at least one regional feature map in the plurality of regional feature maps that corresponds to a person depicted in the image, and generate a target region definition associated with a location of the person using the regional feature map. Based on the target region definition associated with the location of the person, a target regional feature map may be generated by sampling the feature map for the image. The system may process the target regional feature map to generate a keypoint mask and an instance segmentation mask.

    Optimizations for dynamic object instance detection, segmentation, and structure mapping

    公开(公告)号:US10586350B2

    公开(公告)日:2020-03-10

    申请号:US15972035

    申请日:2018-05-04

    Applicant: Facebook, Inc.

    Abstract: In one embodiment, a system accesses pose probability models for predetermined parts of a body depicted in an image. Each of the pose probability models is configured for determining a probability of the associated predetermined body part being at a location in the image. The system determines a candidate pose that is defined by a set of coordinates representing candidate locations of the predetermined body parts. The system further determines a first probability score for the candidate pose based on the pose probability models and the set of coordinates of the candidate pose. A pose representation is generated for the candidate pose using a transformation model and the candidate pose. The system determines a second probability score for the pose representation based on a pose-representation probability model. The system selects the candidate pose to represent a pose of the body based on at least the first and second probability scores.

    Optimizations for Dynamic Object Instance Detection, Segmentation, and Structure Mapping

    公开(公告)号:US20190171903A1

    公开(公告)日:2019-06-06

    申请号:US15971930

    申请日:2018-05-04

    Applicant: Facebook, Inc.

    Abstract: In one embodiment, a system may access an image and generate a feature map for the image using a neural network. The system may identify regions of interest in the feature map. Regional feature maps may be generated for the regions of interest, respectively. Each of the regional feature maps has a first, a second, and a third dimension. The system may generate a first combined regional feature map by combining the regional feature maps. The combined regional feature map has a first, a second, and a third dimension. The system may generate a second combined regional feature map by processing the first combined regional feature map using one or more convolutional layers. The system may generate, for each of the regions of interest, information associated with an object instance based on a portion of the second combined regional feature map associated with that region of interest.

    SYSTEM AND METHOD FOR DETERMINATION OF A DIGITAL DESTINATION BASED ON A MULTI-PART IDENTIFIER

    公开(公告)号:US20190130043A1

    公开(公告)日:2019-05-02

    申请号:US15798179

    申请日:2017-10-30

    Applicant: Facebook, Inc.

    Abstract: One general aspect includes a method, including: capturing an image of an object having a multi-part identifier displayed thereon, the multi-part identifier including a first portion and a second portion, the first portion including graphical content and the second portion including human-recognizable textual content. The method also includes based on the captured image, identifying a domain associated with the graphical content. The method also includes based on the captured image, identifying a sub-part of the domain associated with the textual content. The method also includes identifying a digital destination based on the identified domain and the identified sub-part. The method also includes performing an action based on the digital destination. Other embodiments of this aspect include corresponding computer systems, apparatus, and computer programs recorded on one or more computer storage devices, each configured to perform the actions of the methods.

    ARTIFACT REDUCTION FOR IMAGE STYLE TRANSFER
    7.
    发明申请

    公开(公告)号:US20180300850A1

    公开(公告)日:2018-10-18

    申请号:US15488424

    申请日:2017-04-14

    Applicant: Facebook, Inc.

    CPC classification number: G06N3/08 G06T5/50

    Abstract: An image processing system transforms content images into the style of another reference style image. For example, the system applies a noise mask to generate noisy versions of the content images. The system then recomposes a content image in the style of a reference image by applying computer models to the noisy version of the content image, which reduces artifacts in the stylized image compared to that of a stylized image generated by applying the computer models to the original content image. When the content images are part of a video sequence, the image processing system may adjust the noise mask applied in a subsequent frame such that it tracks the movement of the client device from the current frame to the subsequent frame. This allows the system to reduce artifacts while stylizing the frames of the video in a consistent manner.

    Artifact reduction for image style transfer

    公开(公告)号:US10152768B2

    公开(公告)日:2018-12-11

    申请号:US15488424

    申请日:2017-04-14

    Applicant: Facebook, Inc.

    Abstract: An image processing system transforms content images into the style of another reference style image. For example, the system applies a noise mask to generate noisy versions of the content images. The system then recomposes a content image in the style of a reference image by applying computer models to the noisy version of the content image, which reduces artifacts in the stylized image compared to that of a stylized image generated by applying the computer models to the original content image. When the content images are part of a video sequence, the image processing system may adjust the noise mask applied in a subsequent frame such that it tracks the movement of the client device from the current frame to the subsequent frame. This allows the system to reduce artifacts while stylizing the frames of the video in a consistent manner.

    Generating intermediate views using optical flow

    公开(公告)号:US10057562B2

    公开(公告)日:2018-08-21

    申请号:US15096165

    申请日:2016-04-11

    Applicant: Facebook, Inc.

    Abstract: A canvas generation system generates a canvas view of a scene based on a set of original camera views depicting the scene, for example to recreate a scene in virtual reality. Canvas views can be generated based on a set of synthetic views generated from a set of original camera views. Synthetic views can be generated, for example, by shifting and blending relevant original camera views based on an optical flow across multiple original camera views. An optical flow can be generated using an iterative method which individually optimizes the optical flow vector for each pixel of a camera view and propagates changes in the optical flow to neighboring optical flow vectors.

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