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公开(公告)号：US12254636B2
公开(公告)日：2025-03-18
申请号：US17853799
申请日：2022-06-29
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor： Kunyang Sun , Hao Chen , Chunhua Shen , Youliang Yan , Bin Shao , Songcen Xu
Abstract: An instance segmentation method and apparatus are provided. A to-be-trained segmentation network performs the following processing on each instance group that is in a sample original image and that is of pixels of a marked instance, where each instance group includes at least one marked instance, and the processing includes: predicting at least two different first basic feature maps and a first attention feature map corresponding to each first basic feature map; performing weighted processing on the at least two first basic feature maps and pixel values of respective first attention feature maps corresponding to the at least two first basic feature maps, to obtain a first feature fusion map; and training the to-be-trained segmentation network based on the first feature fusion map and the sample original image. A segmentation model can precisely determine pixels of an instance in an original image.
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公开(公告)号：US12225271B2
公开(公告)日：2025-02-11
申请号：US18070689
申请日：2022-11-29
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor： Bin Shao , Jun Yue , Li Qian , Songcen Xu , Xueyan Huang , Yajiao Liu
Abstract: A video generation method may be applied to the field of image processing and video generation in the field of artificial intelligence. The method includes: receiving a video generation instruction, and obtaining text information and image information in response to the video generation instruction, where the text information includes one or more keywords, and the image information includes N images; obtaining, based on the one or more keywords, one or more image features that is in each of the N images and corresponds to the one or more keywords; and inputting the one or more keywords and the one or more image features of the N images into a target generator network to generate a target video, where the target video includes M images, and the M images are generated based on the one or more image features of the N images and correspond to the one or more keywords.
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公开(公告)号：US12020472B2
公开(公告)日：2024-06-25
申请号：US17388386
申请日：2021-07-29
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor： Xueyi Zou , Yiren Zhou , Songcen Xu , Jianzhuang Liu , Youliang Yan
IPC: G06V10/771 , G06F18/22 , G06T7/246 , G06V10/44 , G06V10/74 , G06V10/75 , G11B27/031
CPC classification number: G06V10/771 , G06F18/22 , G06T7/248 , G06V10/44 , G06V10/759 , G06V10/761 , G11B27/031 , G06T2207/10016 , G06T2207/30242 , G06V2201/07
Abstract: An image processing method. The method includes: An electronic device obtains N images, where the N images have a same quantity of pixels and a same pixel location arrangement, and N is an integer greater than 1; the electronic device obtains, based on feature values of pixels located at a same location in the N images, a reference value of the corresponding location; the electronic device determines a target pixel of each location based on a reference value of the location; and the electronic device generates a target image based on the target pixel of each location.
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公开(公告)号：US20210281754A1
公开(公告)日：2021-09-09
申请号：US17330133
申请日：2021-05-25
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor： Daxin Luo , Fenglong Song , Songcen Xu , Yi Liu , Youliang Yan , Jianzhuang Liu , Li Qian
Abstract: In a method for selecting pictures from a sequence of pictures of an object in motion, a computerized user device determines, for each picture in the sequence of pictures, a value of a motion feature of the object. Based on analyzing the values of the motion feature of the pictures in the sequence, the device identifies a first subset of pictures from the pictures in the sequence. The device then selects, based on a second selection criterion, a second subset of pictures from the first subset of pictures. The pictures in the second subset are displayed to a user for further selection.
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公开(公告)号：US20240331350A1
公开(公告)日：2024-10-03
申请号：US18741072
申请日：2024-06-12
Applicant: Huawei Technologies Co., Ltd.
Inventor： Fei Huang , Xiaofei Wu , Zhihao Li , Songcen Xu , Jianzhuang Liu , Youliang Yan , Li Qian , Xueyan Huang
CPC classification number: G06V10/761 , G06V10/40
Abstract: A method for optimizing a photographing pose of a user, where the method is applied to an electronic device, and the method includes: displaying a photographing interface of a camera of the electronic device; obtaining a to-be-taken image in the photographing interface; determining, based on the to-be-taken image, that the photographing interface includes a portrait; entering a pose recommendation mode; and presenting a recommended human pose picture to a user in a predetermined preview manner, where the human pose picture is at least one picture that is selected from a picture library through metric learning and that has a top-ranked similarity to the to-be-taken image, and where the similarity is an overall similarity obtained by fusing a background similarity and a foreground similarity.
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Patent Agency Ranking
公开(公告)号：US12033369B2
公开(公告)日：2024-07-09
申请号：US17668101
申请日：2022-02-09
Applicant: Huawei Technologies Co., Ltd.
Inventor： Fei Huang , Xiaofei Wu , Zhihao Li , Songcen Xu , Jianzhuang Liu , Youliang Yan , Li Qian , Xueyan Huang
CPC classification number: G06V10/761 , G06V10/40
Abstract: A method for optimizing a photographing pose of a user, where the method is applied to an electronic device, and the method includes: displaying a photographing interface of a camera of the electronic device; obtaining a to-be-taken image in the photographing interface; determining, based on the to-be-taken image, that the photographing interface includes a portrait; entering a pose recommendation mode; and presenting a recommended human pose picture to a user in a predetermined preview manner, where the human pose picture is at least one picture that is selected from a picture library through metric learning and that has a top-ranked similarity to the to-be-taken image, and where the similarity is an overall similarity obtained by fusing a background similarity and a foreground similarity.
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公开(公告)号：US12259922B2
公开(公告)日：2025-03-25
申请号：US18548039
申请日：2021-12-20
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor： Lei Hao , Yu Wang , Min Wang , Songcen Xu , Weicai Zhong , Zhenhua Zhao
IPC: G06F16/53 , G06F16/538 , G06F16/583
Abstract: In one example method, a first image including M objects is obtained. For N objects in the M objects, when N is greater than or equal to 2, arrangement orders of the N objects is determined, where an arrangement order of any one of the N objects is determined based on at least one of a scene intent weight, a confidence score, or an object relationship score. The scene intent weight is used to indicate a probability that the any object is searched in a scene corresponding to the first image, the confidence score is a similarity between the any object and an image in an image library, and the object relationship score is used to indicate importance of the any object in the first image. Search results of some or all of the N objects are fed back according to the arrangement orders of the N objects.
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公开(公告)号：US20230089566A1
公开(公告)日：2023-03-23
申请号：US18070689
申请日：2022-11-29
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor： Bin Shao , Jun Yue , Li Qian , Songcen Xu , Xueyan Huang , Yajiao Liu
Abstract: A video generation method, may be applied to the field of image processing and video generation in the field of artificial intelligence. The method includes: receiving a video generation instruction, and obtaining text information and image information in response to the video generation instruction, where the text information includes one or more keywords, and the image information includes N images; obtaining, based on the one or more keywords, an image feature that is in each of the N images and that corresponds to the one or more keywords; and inputting the one or more keywords and image features of the N images into a target generator network to generate a target video, where the target video includes M images, and the M images are images that are generated based on the image features of the N images and that correspond to the one or more keywords.
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公开(公告)号：US20220245926A1
公开(公告)日：2022-08-04
申请号：US17668101
申请日：2022-02-09
Applicant: Huawei Technologies Co., Ltd.
Inventor： Fei Huang , Xiaofei Wu , Zhihao Li , Songcen Xu , Jianzhuang Liu , Youliang Yan , Li Qian , Xueyan Huang
Abstract: A method for optimizing a photographing pose of a user, where the method is applied to an electronic device, and the method includes: displaying a photographing interface of a camera of the electronic device; obtaining a to-be-taken image in the photographing interface; determining, based on the to-be-taken image, that the photographing interface includes a portrait; entering a pose recommendation mode; and presenting a recommended human pose picture to a user in a predetermined preview manner, where the human pose picture is at least one picture that is selected from a picture library through metric learning and that has a top-ranked similarity to the to-be-taken image, and where the similarity is an overall similarity obtained by fusing a background similarity and a foreground similarity.
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公开(公告)号：US20220012533A1
公开(公告)日：2022-01-13
申请号：US17484545
申请日：2021-09-24
Applicant: Huawei Technologies Co., Ltd.
Inventor： Jun Yue , Jianzhuang Liu , Songcen Xu , Youliang Yan , Li Qian
Abstract: This application discloses an object recognition method and apparatus in the field of artificial intelligence. This application relates to the field of artificial intelligence, and specifically, to the field of computer vision. The method includes: obtaining one or more body regions of a to-be-recognized image; determining a saliency score of each of the one or more body regions; and when a saliency score of a body region A is greater than or equal to a categorization threshold, determining a feature vector of an object in the body region A based on a feature of the object in the body region A, and determining a category of the object in the body region A based on the feature vector of the object in the body region A and a category feature vector in a feature library, where the body region A is any one of the one or more body regions.
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