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公开(公告)号:US11881044B2
公开(公告)日:2024-01-23
申请号:US17353540
申请日:2021-06-21
Inventor: Chengquan Zhang , Mengyi En , Ju Huang , Qunyi Xie , Xiameng Qin , Kun Yao , Junyu Han , Jingtuo Liu , Errui Ding
IPC: G06V30/414 , G06T7/136 , G06T7/11 , G06F18/213 , G06V30/146 , G06V30/18 , G06V10/764 , G06V10/82 , G06V30/10
CPC classification number: G06V30/414 , G06F18/213 , G06T7/11 , G06T7/136 , G06V10/764 , G06V10/82 , G06V30/147 , G06V30/18057 , G06T2207/30176 , G06V30/10
Abstract: A method and apparatus for processing an image, a device and a storage medium are provided. An implementation of the method includes: acquiring a template image, the template image including at least one region of interest; determining a first feature map corresponding to each region of interest in the template image; acquiring a target image; determining a second feature map of the target image; and determining at least one region of interest in the target image according to the first feature map and the second feature map.
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22.
公开(公告)号:US11763552B2
公开(公告)日:2023-09-19
申请号:US17116597
申请日:2020-12-09
Inventor: Shufei Lin , Jianfeng Zhu , Pengcheng Yuan , Bin Zhang , Shumin Han , Yingbo Xu , Yuan Feng , Ying Xin , Xiaodi Wang , Jingwei Liu , Shilei Wen , Hongwu Zhang , Errui Ding
IPC: G06V10/82 , G06N3/088 , G06T7/00 , G06F18/214 , G06N3/045 , G06V10/776 , G06V20/60
CPC classification number: G06V10/82 , G06F18/2148 , G06N3/045 , G06N3/088 , G06T7/0004 , G06V10/776 , G06V20/60 , G06T2207/20081 , G06T2207/20084 , G06T2207/30124
Abstract: A method for detecting a surface defect, a method for training model, an apparatus, a device, and a medium, are provided. The method includes: inputting a surface image of the article for detection into a defect detection model to perform a defect detection, and acquiring a defect detection result output by the defect detection model; inputting a surface image of a defective article determined to be defective into an image discrimination model based on the defect detection result to determine whether the surface image of the defective article is defective, wherein the image discrimination model is a trained generative adversarial networks model, and the generative adversarial networks model is obtained by training using a surface image of a defect-free good article; and adjusting the defect detection result of the surface image of the defective article according to a determination result of the image discrimination model.
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公开(公告)号:US11610389B2
公开(公告)日:2023-03-21
申请号:US17201665
申请日:2021-03-15
Inventor: Jian Wang , Zipeng Lu , Hao Sun , Hongwu Zhang , Shilei Wen , Errui Ding
IPC: G06T7/73 , G06V10/46 , G06N3/04 , G06F18/213 , G06V10/764 , G06V10/82 , G06V40/20
Abstract: A method and apparatus for positioning a key point, a device, and a storage medium are provided. The method may include: extracting a first feature map and a second feature map of a to-be-positioned image, the first feature map and the second feature map being different feature maps; determining, based on the first feature map, an initial position of a key point in the to-be-positioned image; determining, based on the second feature map, an offset of the key point; and adding the initial position of the key point with the offset of the key point to obtain a final position of the key point.
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公开(公告)号:US11514263B2
公开(公告)日:2022-11-29
申请号:US16869024
申请日:2020-05-07
Inventor: Wei Zhang , Xiao Tan , Hao Sun , Shilei Wen , Errui Ding
IPC: G06K9/62 , G06N3/04 , G06N3/08 , G06V10/44 , G06V10/80 , G06V10/82 , G06V40/16 , G06V10/26 , G06V10/22
Abstract: Embodiments of the present disclosure disclose a method and apparatus for processing an image. A specific embodiment of the method includes: acquiring a feature map of a target image, where the target image contains a target object; determining a local feature map of a target size in the feature map; combining features of different channels in the local feature map to obtain a local texture feature map; and obtaining location information of the target object based on the local texture feature map.
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公开(公告)号:US20220270373A1
公开(公告)日:2022-08-25
申请号:US17743410
申请日:2022-05-12
Inventor: Xipeng Yang , Minyue Jiang , Xiao Tan , Hao Sun , Shilei Wen , Hongwu Zhang , Errui Ding
IPC: G06V20/52 , G06V10/40 , G06V10/764 , G06V10/774 , G06V10/22
Abstract: A method, an electronic device and a storage medium are provided. The method may include: acquiring a to-be-inspected image; inputting the to-be-inspected image into a pre-established vehicle detection model to obtain a vehicle detection result, where the vehicle detection result includes category information, coordinate information, coordinate reliabilities, and coordinate error information of detection boxes, and the vehicle detection model is configured for characterizing a corresponding relationship between images and vehicle detection results; selecting, based on the coordinate reliabilities of the detection boxes, a detection box from the vehicle detection result for use as a to-be-processed detection box; and generating, based on coordinate information and coordinate error information of the to-be-processed detection box, coordinate information of a processed detection box.
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公开(公告)号:US11256920B2
公开(公告)日:2022-02-22
申请号:US16830895
申请日:2020-03-26
Inventor: Xiang Long , Dongliang He , Fu Li , Zhizhen Chi , Zhichao Zhou , Xiang Zhao , Ping Wang , Hao Sun , Shilei Wen , Errui Ding
Abstract: A method and an apparatus for classifying a video are provided. The method may include: acquiring a to-be-classified video; extracting a set of multimodal features of the to-be-classified video; inputting the set of multimodal features into a post-fusion model corresponding to each modal respectively, to obtain multimodal category information of the to-be-classified video; and fusing the multimodal category information of the to-be-classified video, to obtain category information of the to-be-classified video. This embodiment improves the accuracy of video classification.
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公开(公告)号:US20210174537A1
公开(公告)日:2021-06-10
申请号:US16894123
申请日:2020-06-05
Inventor: Xiaoqing Ye , Xiao Tan , Wei Zhang , Hao Sun , Errui Ding
Abstract: Embodiments of the present disclosure provide a method and apparatus for detecting a target object in an image. The method includes: performing following prediction operations using a pre-trained neural network: detecting a target object in a two-dimensional image to determine a two-dimensional bounding box of the target object; and determining a relative position constraint relationship between the two-dimensional bounding box of the target object and a three-dimensional projection bounding box obtained by projecting a three-dimensional bounding box of the target object into the two-dimensional image; and the method further including: determining the three-dimensional projection bounding box of the target object, based on the two-dimensional bounding box of the target object and the relative position constraint relationship between the two-dimensional bounding box of the target object and the three-dimensional projection bounding box.
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公开(公告)号:US20210064919A1
公开(公告)日:2021-03-04
申请号:US16869024
申请日:2020-05-07
Inventor: Wei Zhang , Xiao Tan , Hao Sun , Shilei Wen , Errui Ding
Abstract: Embodiments of the present disclosure disclose a method and apparatus for processing an image. A specific embodiment of the method includes: acquiring a feature map of a target image, where the target image contains a target object; determining a local feature map of a target size in the feature map; combining features of different channels in the local feature map to obtain a local texture feature map; and obtaining location information of the target object based on the local texture feature map.
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公开(公告)号:US20200327384A1
公开(公告)日:2020-10-15
申请号:US16710528
申请日:2019-12-11
Inventor: Chengquan Zhang , Zuming Huang , Mengyi En , Junyu Han , Errui Ding
Abstract: Embodiments of the present disclosure provide a method and apparatus for detecting text regions in an image, a device, and a medium. The method may include: detecting, based on feature representation of an image, a first text region in the image, where the first text region covers a text in the image, a region occupied by the text being of a certain shape; determining, based on a feature block of the first text region, text geometry information associated with the text, where the text geometry information includes a text centerline of the text and distance information of the centerline from the upper and lower borders of the text; and adjusting, based on the text geometry information associated with the text, the first text region to a second text region, where the second text region also covers the text and is smaller than the first text region.
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