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公开(公告)号：US20230213388A1
公开(公告)日：2023-07-06
申请号：US17998881
申请日：2020-10-14
Inventor： Haocheng Feng , Haixiao Yue , Keyao Wang , Gang Zhang , Yanwen Fan , Xiyu Yu , Junyu Han , Jingtuo Liu , Errui Ding , Haifeng Wang
IPC: G01J5/00
CPC classification number: G01J5/0025 , G01J2005/0077
Abstract: A method and an apparatus for measuring temperature, and a computer-readable storage medium includes detecting a target position of an object in an input image; determining key points of the target position and weight information of each key point based on a detection result of the target position, in which the weight information is configured to indicate a probability of each key point being covered; acquiring temperature information of each key point; and determining a temperature of the target position at least based on the temperature information and the weight information of each key point.
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公开(公告)号：US20230186486A1
公开(公告)日：2023-06-15
申请号：US17995752
申请日：2020-10-30
Inventor： Wei Zhang , Xiao Tan , Hao Sun , Shilei Wen , Hongwu Zhang , Errui Ding
CPC classification number: G06T7/20 , G06V10/25 , G06V10/44 , G06V10/761 , G06V10/762 , G06V20/46 , G06T9/00 , G06V2201/08 , G06T2207/30241 , G06T2207/30252
Abstract: A method for tracking vehicles includes: extracting a target image at a current moment from a video stream obtained during traveling of vehicles; performing instance segmentation on the target image to obtain detection boxes corresponding to individual vehicles in the target image; extracting, from the detection box for each vehicle, a set of pixel points corresponding to each vehicle; processing image features of each pixel point in the set of pixel points corresponding to each vehicle to determine features of each vehicle in the target image; and determining, according to the features of each vehicle in the target image and the degree of matching between the features of each vehicle in past images, movement trajectory of each vehicle in the target image, wherein the past images are n images adjacent to and before the target image in the video stream, and n is a positive integer.
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3.发明申请公开(公告)号：US20230009547A1
公开(公告)日：2023-01-12
申请号：US17933271
申请日：2022-09-19
Inventor： Xipeng Yang , Xiao Tan , Hao Sun , Errui Ding
IPC: G06V10/77 , G06V10/80 , G06V10/764 , G06V10/26
Abstract: A method for detecting an object based on a video includes: obtaining a plurality of image frames of a video to be detected; obtaining initial feature maps by extracting features of the plurality of image frames; for each two adjacent image frames of the plurality of image frames, obtaining a target feature map of a latter image frame of the two adjacent image frames by performing feature fusing on the sub-feature maps of the first target dimensions included in the initial feature map of a former image frame of the two adjacent image frames and the sub-feature maps of the second target dimensions included in the initial feature map of the latter image frame; and performing object detection on the respective target feature map of each image frame.
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公开(公告)号：US12260492B2
公开(公告)日：2025-03-25
申请号：US18099602
申请日：2023-01-20
Inventor： Di Wang , Ruizhi Chen , Chen Zhao , Jingtuo Liu , Errui Ding , Tian Wu , Haifeng Wang
Abstract: A method for training a three-dimensional face reconstruction model includes inputting an acquired sample face image into a three-dimensional face reconstruction model to obtain a coordinate transformation parameter and a face parameter of the sample face image; determining the three-dimensional stylized face image of the sample face image according to the face parameter of the sample face image and the acquired stylized face map of the sample face image; transforming the three-dimensional stylized face image of the sample face image into a camera coordinate system based on the coordinate transformation parameter, and rendering the transformed three-dimensional stylized face image to obtain a rendered map; and training the three-dimensional face reconstruction model according to the rendered map and the stylized face map of the sample face image.
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公开(公告)号：US11893708B2
公开(公告)日：2024-02-06
申请号：US17505889
申请日：2021-10-20
Inventor： Jian Wang , Xiang Long , Hao Sun , Zhiyong Jin , Errui Ding
IPC: G06K9/00 , G06T3/40 , G06F18/213 , G06F18/25 , G06N3/045
CPC classification number: G06T3/4046 , G06F18/213 , G06F18/253 , G06N3/045
Abstract: Provided are an image processing method and apparatus, a device, and a storage medium, relating to the technical field of image processing, in particular to the artificial intelligence fields such as computer vision and deep learning. The specific implementation scheme is as follows: inputting a to-be-processed image into an encoding network to obtain a basic image feature, wherein the encoding network includes at least two cascaded overlapping encoding sub-networks which perform encoding and fusion processing on input data at at least two resolutions; and inputting the basic image feature into a decoding network to obtain a target image feature for pixel point classification, wherein the decoding network includes at least one cascaded overlapping decoding sub-network to perform decoding and fusion processing on input data at at least two resolutions respectively.
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Patent Agency Ranking
公开(公告)号：US11694436B2
公开(公告)日：2023-07-04
申请号：US17164681
申请日：2021-02-01
Inventor： Minyue Jiang , Xiao Tan , Hao Sun , Hongwu Zhang , Shilei Wen , Errui Ding
CPC classification number: G06V20/20 , G06N3/045 , G06T7/97 , G06V20/176 , G06V20/56
Abstract: The present application discloses a vehicle re-identification method and apparatus, a device and a storage medium, which relates to the field of computer vision, intelligent search, deep learning and intelligent transportation. The specific implementation scheme is: receiving a re-identification request from a terminal device, the re-identification request including a first image of a first vehicle shot by a first camera and information of the first camera; acquiring a first feature of the first vehicle and a first head orientation of the first vehicle according to the first image; determining a second image of the first vehicle from images of multiple vehicles according to the first feature, multiple second features extracted based on the images of the multiple vehicles in an image database, the first head orientation of the first vehicle, and the information of the first camera; and transmitting the second image to the terminal device.
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公开(公告)号：US11610388B2
公开(公告)日：2023-03-21
申请号：US17164613
申请日：2021-02-01
Inventor： Mingyuan Mao , Yuan Feng , Ying Xin , Pengcheng Yuan , Bin Zhang , Shufei Lin , Xiaodi Wang , Shumin Han , Yingbo Xu , Jingwei Liu , Shilei Wen , Hongwu Zhang , Errui Ding
IPC: G06V10/44 , G06T7/73 , G06N3/08 , G06V40/10 , G06V20/52 , G06F18/22 , G06V10/764 , G06V10/778 , G06V10/82
Abstract: The present application discloses a method and an apparatus for detecting wearing of a safety helmet, a device and a storage medium. The method for detecting wearing of a safety helmet includes: acquiring a first image collected by a camera device, where the first image includes at least one human body image; determining the at least one human body image and at least one head image in the first image; determining a human body image corresponding to each head image in the at least one human body image according to an area where the at least one human body image is located and an area where the at least one head image is located; and processing the human body image corresponding to the at least one head image according to a type of the at least one head image.
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公开(公告)号：US20210192194A1
公开(公告)日：2021-06-24
申请号：US17022219
申请日：2020-09-16
Inventor： Zhizhen Chi , Fu Li , Hao Sun , Dongliang He , Xiang Long , Zhichao Zhou , Ping Wang , Shilei Wen , Errui Ding
Abstract: The present application discloses a video-based human behavior recognition method, apparatus, device and storage medium, and relates to the technical field of human recognitions. The specific implementation scheme lies in: acquiring a human rectangle of each video frame of the video to be recognized, where each human rectangle includes a plurality of human key points, and each of the human key points has a key point feature; constructing a feature matrix according to the human rectangle of the each video frame; convolving the feature matrix with respect to a video frame quantity dimension to obtain a first convolution result and convolving the feature matrix with respect to a key point quantity dimension to obtain a second convolution result; inputting the first convolution result and the second convolution result into a preset classification model to obtain a human behavior category of the video to be recognized.
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公开(公告)号：US20230419592A1
公开(公告)日：2023-12-28
申请号：US18099602
申请日：2023-01-20
Inventor： Di WANG , Ruizhi Chen , Chen Zhao , Jingtuo Liu , Errui Ding , Tian Wu , Haifeng Wang
CPC classification number: G06T15/20 , G06V40/168 , G06T15/04 , G06T15/40 , G06T19/20 , G06V10/82 , G06V10/774 , G06T2219/2004 , G06T2219/2012 , G06T2219/2016
Abstract: A method for training a three-dimensional face reconstruction model includes inputting an acquired sample face image into a three-dimensional face reconstruction model to obtain a coordinate transformation parameter and a face parameter of the sample face image; determining the three-dimensional stylized face image of the sample face image according to the face parameter of the sample face image and the acquired stylized face map of the sample face image; transforming the three-dimensional stylized face image of the sample face image into a camera coordinate system based on the coordinate transformation parameter, and rendering the transformed three-dimensional stylized face image to obtain a rendered map; and training the three-dimensional face reconstruction model according to the rendered map and the stylized face map of the sample face image.
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公开(公告)号：US20230120985A1
公开(公告)日：2023-04-20
申请号：US18083313
申请日：2022-12-16
Inventor： Yanwen Fan , Xiyu Yu , Gang Zhang , Jingtuo Liu , Haifeng Wang , Errui Ding , Junyu Han
IPC: G06V10/774 , G06V40/16 , G06V10/26 , G06V10/77
Abstract: A method for training a face recognition model includes: acquiring a plurality of first training images being uncovered face images, and acquiring a plurality of covering object images; generating a plurality of second training images by separately fusing the plurality of covering object images with the uncovered face images; and training the face recognition model by inputting the plurality of first training images and the plurality of second training images into the face recognition model.
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