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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.
Inventor: Peter Vajda , Peizhao Zhang , Fei Yang , Yanghan Wang
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.
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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.
Inventor: Peter Vajda , Peizhao Zhang , Fei Yang , Yanghan Wang
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.
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3.
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.
Inventor: Peter Vajda , Peizhao Zhang , Fei Yang , Yanghan Wang
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.
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4.
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.
Inventor: Maria Ioveva , Matthew William Canton , Peizhao Zhang , Shihang Wei , Shen Wang , Peter Vajda , Han Wang
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.
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5.
公开(公告)号:US10650072B2
公开(公告)日:2020-05-12
申请号:US15798179
申请日:2017-10-30
Applicant: Facebook, Inc.
Inventor: Maria Loveva , Matthew William Canton , Peizhao Zhang , Shihang Wei , Shen Wang , Peter Vajda , Han Wang
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.
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公开(公告)号:US20190171871A1
公开(公告)日:2019-06-06
申请号:US16236974
申请日:2018-12-31
Applicant: Facebook, Inc.
Inventor: Peizhao Zhang , Peter Vajda , Kevin Matzen , Ross Girshick
Abstract: In one embodiment, a system may access first, second, and third probability models that are respectively associated with predetermined first and second body parts and a predetermined segment connecting the first and second body parts. Each model includes probability values associated with regions in an image, with each value representing the probability of the associated region containing the associated body part or segment. The system may select a first and second region based on the first probability model and a third region based on the second probability model. Based on the third probability model, the system may compute a first probability score for regions connecting the first and third regions and a second probability score for regions connecting the second and third regions. Based on the first and second probability scores, the system may select the first region to indicate where the predetermined first body part appears in the image.
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公开(公告)号:US10796452B2
公开(公告)日:2020-10-06
申请号:US16236877
申请日:2018-12-31
Applicant: Facebook, Inc.
Inventor: Peter Vajda , Peizhao Zhang , Matthieu Tony Uyttendaele , Yanghan Wang
Abstract: In one embodiment, a system accesses a probability model associated with an image depicting a body. The probability model includes probability values associated with regions of the image and each probability value represents a probability of the associated region of the image containing a particular body part. The system selects a subset (e.g., 3) of the probability values based on a comparison of the probability values. For each selected probability value, the system identifies surrounding probability values surrounding the selected probability value and computes a probabilistic maximum based on the selected probability value and the surrounding probability values. Each probabilistic maximum is associated with a location within the regions associated with the selected probability value and the surrounding probability values. One of the locations associated with the probabilistic maxima is then selected, which represents a determined location in the image that corresponds to the particular body part in the image.
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公开(公告)号:US10733431B2
公开(公告)日:2020-08-04
申请号:US16236974
申请日:2018-12-31
Applicant: Facebook, Inc.
Inventor: Peizhao Zhang , Peter Vajda , Kevin Matzen , Ross Girshick
Abstract: In one embodiment, a system may access first, second, and third probability models that are respectively associated with predetermined first and second body parts and a predetermined segment connecting the first and second body parts. Each model includes probability values associated with regions in an image, with each value representing the probability of the associated region containing the associated body part or segment. The system may select a first and second region based on the first probability model and a third region based on the second probability model. Based on the third probability model, the system may compute a first probability score for regions connecting the first and third regions and a second probability score for regions connecting the second and third regions. Based on the first and second probability scores, the system may select the first region to indicate where the predetermined first body part appears in the image.
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公开(公告)号:US10692243B2
公开(公告)日:2020-06-23
申请号:US15971930
申请日:2018-05-04
Applicant: Facebook, Inc.
Inventor: Peter Vajda , Peizhao Zhang , Fei Yang , Yanghan Wang
IPC: G06K9/00 , G06T7/73 , G06K9/46 , G06T7/11 , G06N3/04 , G06N3/08 , G06K9/62 , G06K9/32 , G06N5/02
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.
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公开(公告)号:US20190172224A1
公开(公告)日:2019-06-06
申请号:US16236877
申请日:2018-12-31
Applicant: Facebook, Inc.
Inventor: Peter Vajda , Peizhao Zhang , Matthieu Tony Uyttendaele , Yanghan Wang
IPC: G06T7/77
CPC classification number: G06T7/77 , G06N3/0454 , G06N3/084 , G06N5/022 , G06T2207/20076 , G06T2207/30196
Abstract: In one embodiment, a system accesses a probability model associated with an image depicting a body. The probability model includes probability values associated with regions of the image and each probability value represents a probability of the associated region of the image containing a particular body part. The system selects a subset (e.g., 3) of the probability values based on a comparison of the probability values. For each selected probability value, the system identifies surrounding probability values surrounding the selected probability value and computes a probabilistic maximum based on the selected probability value and the surrounding probability values. Each probabilistic maximum is associated with a location within the regions associated with the selected probability value and the surrounding probability values. One of the locations associated with the probabilistic maxima is then selected, which represents a determined location in the image that corresponds to the particular body part in the image.
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