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公开(公告)号：US11587338B2
公开(公告)日：2023-02-21
申请号：US17211491
申请日：2021-03-24
Inventor： Xiaoqing Ye , Xiao Tan , Hao Sun , Hongwu Zhang
Abstract: The present disclosure provides a three-dimensional (3D) object detection method, a 3D object detection apparatus, an electronic device, and a readable storage medium, belonging to a field of computer vision technologies. Two-dimensional (2D) image parameters and initial 3D image parameters are determined for a target object. Candidate 3D image parameters are determined for the target object based on a disturbance range of 3D parameters and the initial 3D image parameters determined for the target object. Target 3D image parameters are selected for the target object from the candidate 3D image parameters determined for the target object based on the 2D image parameters. A 3D detection result of the target object is determined based on the target 3D image parameters.
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公开(公告)号：US20210319579A1
公开(公告)日：2021-10-14
申请号：US17179456
申请日：2021-02-19
Inventor： Xiaoqing Ye , Xiao Tan , Hao Sun , Hongwu Zhang
Abstract: Embodiments of the present disclosure disclose a method and apparatus for generating position information, a device and a medium. A specific embodiment of the method includes: acquiring an image and vehicle position information, wherein the image includes a target element; inputting the image into a pre-established depth map generation model to obtain a first depth map, wherein the focal length of sample images of sample data used during the training of the model is a sample focal length; generating a second depth map based on the sample focal length, the first depth map, and an estimated focal length of the image; determining depth information of the target element according to element position information of the target element in the image and the second depth map; and generating position information of the target element based on the vehicle position information and the depth information of the target element.
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公开(公告)号：US11463631B2
公开(公告)日：2022-10-04
申请号：US17025255
申请日：2020-09-18
Inventor： Henan Zhang , Xin Li , Fu Li , Tianwei Lin , Hao Sun , Shilei Wen , Hongwu Zhang , Errui Ding
Abstract: Embodiments of the present disclosure provide a method and apparatus for generating an image. The method may include: receiving a first image including a face input by a user in an interactive scene; presenting the first image to the user; inputting the first image into a pre-trained generative adversarial network in a backend to obtain a second image output by the generative adversarial network; where the generative adversarial network uses face attribute information generated based on the input image as a constraint; and presenting the second image to the user in response to obtaining the second image output by the generative adversarial network in the backend.
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公开(公告)号：US20220270289A1
公开(公告)日：2022-08-25
申请号：US17743402
申请日：2022-05-12
Inventor： Wei Zhang , Xiaoqing Ye , Xiao Tan , Hao Sun , Shilei Wen , Hongwu Zhang , Errui Ding
IPC: G06T7/73 , G06T7/194 , G06T7/593 , H04N13/128
Abstract: A method and device for detecting a vehicle pose, relating to the fields of computer vision and automatic driving. The specific implementation solution comprises: inputting a vehicle left view point image and a vehicle right view point image into a part prediction and mask segmentation network model, and determining foreground pixel points and part coordinates thereof in a reference image; converting coordinates of the foreground pixels in the reference image into coordinates of the foreground pixels in a camera coordinate system so as to obtain a pseudo-point cloud, and fusing part coordinate of the foreground pixels and the pseudo-point cloud to obtain fused pseudo-point cloud; and inputting the fused pseudo-point cloud into a pre-trained pose prediction model to obtain a pose information of the vehicle to be detected.
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公开(公告)号：US11363271B2
公开(公告)日：2022-06-14
申请号：US17125370
申请日：2020-12-17
Inventor： Chao Li , Yukang Ding , Dongliang He , Fu Li , Hao Sun , Shilei Wen , Hongwu Zhang , Errui Ding
IPC: H04N19/132 , H04N19/172 , G06K9/62 , G06N3/04
Abstract: A method for video frame interpolation, a related electronic device and a storage medium is disclosed. A video is obtained. An (i−1)th frame and an ith frame of the video are obtained. Visual semantic feature maps and depth maps of the (i−1)th frame and the ith frame are obtained. Frame interpolation information is obtained based on the visual semantic feature maps and the depth maps. An interpolated frame between the (i−1)th frame and the ith frame is generated based on the frame interpolation information and the (i−1)th frame and is inserted between the (i−1)th frame and the ith frame.
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Patent Agency Ranking
公开(公告)号：US11915466B2
公开(公告)日：2024-02-27
申请号：US17338328
申请日：2021-06-03
Inventor： Xipeng Yang , Xiao Tan , Hao Sun , Hongwu Zhang
IPC: G06T7/246 , G06V10/44 , G06T7/215 , G06T7/73 , G06F18/213 , G06V10/25 , G06V30/19 , G06V30/24 , G06V10/82
CPC classification number: G06V10/454 , G06F18/213 , G06T7/215 , G06T7/246 , G06T7/74 , G06V10/25 , G06V10/82 , G06V30/19173 , G06V30/2504 , G06T2207/20016 , G06T2207/20081 , G06V2201/07
Abstract: Embodiments of the present disclosure disclose a method and apparatus for determining a target anchor, a device and a storage medium. The method may include: extracting a plurality of feature maps of an original image using a feature extraction network; inputting the plurality of feature maps into a feature pyramid network to perform feature fusion, to obtain a plurality of fused feature maps; and using a region proposal network to implement operations as follows: determining an initial anchor of a network head using the fused feature map, based on a size of each fused feature map, and determining an offset parameter of the initial anchor, based on a ratio of the size of the fused feature map to the original image, and generating a plurality of candidate anchors in different directions, based on the offset parameter of the initial anchor.
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7.发明授权公开(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：US11557062B2
公开(公告)日：2023-01-17
申请号：US17172883
申请日：2021-02-10
Inventor： Xiaoqing Ye , Xiao Tan , Hao Sun , Hongwu Zhang
Abstract: Embodiments of the present disclosure provide a method and apparatus for processing a video frame, and relates to the field of computer vision technology. The method may include: acquiring a plurality of candidate first-order radial distortion parameters preset for a to-be-processed video frame, and acquiring a specified value of a specified radial distortion parameter; performing radial distortion correction on the to-be-processed video frame to obtain a first initial corrected video frame; selecting a first initial corrected video frame in which a local region except for a center region after distortion correction includes a largest number of straight line segments; and determining a candidate first-order radial distortion parameter corresponding to the selected first initial corrected video frame for use as a target first-order radial distortion parameter of the to-be-processed video frame.
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公开(公告)号：US11521331B2
公开(公告)日：2022-12-06
申请号：US17179456
申请日：2021-02-19
Inventor： Xiaoqing Ye , Xiao Tan , Hao Sun , Hongwu Zhang
Abstract: Embodiments of the present disclosure disclose a method and apparatus for generating position information, a device and a medium. A specific embodiment of the method includes: acquiring an image and vehicle position information, wherein the image includes a target element; inputting the image into a pre-established depth map generation model to obtain a first depth map, wherein the focal length of sample images of sample data used during the training of the model is a sample focal length; generating a second depth map based on the sample focal length, the first depth map, and an estimated focal length of the image; determining depth information of the target element according to element position information of the target element in the image and the second depth map; and generating position information of the target element based on the vehicle position information and the depth information of the target element.
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