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31.发明申请公开(公告)号：US20210272306A1
公开(公告)日：2021-09-02
申请号：US17324174
申请日：2021-05-19
Inventor： Minyue JIANG , Xipeng YANG , Xiao TAN , Hao SUN
Abstract: The present application discloses a method for training an image depth estimation model, a method and apparatus for processing image depth information, an automatic driving vehicle, an electronic device, a program product, a storage medium, which includes: inputting a sample environmental image, sample environmental point cloud data and sample edge information of the sample environmental image into a to-be-trained model; and determining initial depth information of each of pixel points in the sample environmental image and a feature relationship between each of the pixel points and a corresponding neighboring pixel point of each of the pixel points through the to-be-trained model, and optimizing the initial depth information of each of the pixel points according to the feature relationship to obtain optimized depth information of each of the pixel points, and adjusting a parameter of the to-be-trained model according to the optimized depth information to obtain the image depth estimation model.
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公开(公告)号：US20250069345A1
公开(公告)日：2025-02-27
申请号：US17917518
申请日：2022-04-21
Inventor： Bo JU , Xiaoqing YE , Xiao TAN , Hao SUN
Abstract: Disclosed are a method for generating point cloud data, an electronic device and a storage medium. The method includes: acquiring a set of real point clouds for a target object based on a LiDAR; performing image acquisition on the target object, and generating a set of pseudo point clouds based on an acquired image; and generating the set of target point clouds for model training by fusing the set of real point clouds and the set of pseudo point clouds.
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公开(公告)号：US20240144570A1
公开(公告)日：2024-05-02
申请号：US17794081
申请日：2022-01-29
Inventor： Qu CHEN , Xiaoqing YE , Xiao TAN , Hao SUN
Abstract: A method and apparatus for generating a drivable 3D character, an electronic device and a storage medium are disclosed, which relate to the field of artificial intelligence, such as computer vision, deep learning, or the like, and may be applied to 3D vision and other scenarios. The method may include: acquiring a 3D human body mesh model corresponding to a to-be-processed 2D image; performing a skeleton embedding operation on the 3D human body mesh model; and performing a skin binding operation on the 3D human body mesh model after the skeleton embedding operation to obtain a drivable 3D human body mesh model.
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公开(公告)号：US20230245339A1
公开(公告)日：2023-08-03
申请号：US17884275
申请日：2022-08-09
Inventor： Guanying CHEN , Xiaoqing YE , Xiao TAN , Hao SUN
CPC classification number: G06T7/73 , G06V20/46 , G06T19/20 , G06T2207/20081 , G06T2219/2004
Abstract: Provided are a method for adjusting a three-dimensional pose, an electronic device, and a storage medium, relates to the field of artificial intelligence, and specifically to computer vision and deep learning technologies. A specific implementation solution includes acquiring a video currently recorded; estimating multiple two-dimensional key points of a virtual three-dimensional model and an initial three-dimensional pose based on multiple image frames; performing contact detection on a target part of the virtual three-dimensional model by using the multiple two-dimensional key points, to obtain a detection result; determining multiple target three-dimensional key points by means of the detection result and multiple initial three-dimensional key points corresponding to the initial three-dimensional pose; and adjusting the initial three-dimensional pose to a target three-dimensional pose by using the multiple initial three-dimensional key points and the multiple target three-dimensional key points.
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公开(公告)号：US20230102422A1
公开(公告)日：2023-03-30
申请号：US17807375
申请日：2022-06-16
Inventor： Desen ZHOU , Jian WANG , Hao SUN
Abstract: Provided is an image recognition method. The method includes determining subject decoded features of a to-be-detected image and an original interaction decoded feature of a subject interactive relationship in the to-be-detected image; determining subject decoded features associated with the original interaction decoded feature, and updating the original interaction decoded feature by using the associated subject decoded features so as to obtain a new interaction decoded feature; and according to the subject decoded features of the to-be-detected image and the new interaction decoded feature, determining at least two subjects to which the subject interactive relationship in the to-be-detected belongs.
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Patent Agency Ranking
公开(公告)号：US20230051232A1
公开(公告)日：2023-02-16
申请号：US17976673
申请日：2022-10-28
Inventor： Desen ZHOU , Jian WANG , Hao SUN
Abstract: A human-object interaction detection method, a neural network and a training method therefor is provided. The human-object interaction detection method includes: performing first target feature extraction on an image feature of an image; performing first interaction feature extraction on the image feature; processing a plurality of first target features to obtain target information of a plurality of detected targets; processing one or more first interaction features to obtain motion information of a motion, human information of a human target corresponding to each motion, and object information of an object target corresponding to each motion; matching the plurality of detected targets with one or more motions; and updating human information of a corresponding human target based on target information of a detected target matching the corresponding human target, and updating object information of a corresponding object target based on target information of a detected target matching the corresponding object target.
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公开(公告)号：US20220366589A1
公开(公告)日：2022-11-17
申请号：US17876408
申请日：2022-07-28
Inventor： Zhikang ZOU , Xiaoqing YE , Hao SUN
Abstract: A method of determining disparity is provided. The implementation scheme is: obtaining a plurality of images corresponding to a target view, wherein each image in the plurality of images is obtained by performing size adjustment on the target view, and each image in the plurality of images has the same size as a feature map output by a corresponding layer structure in a disparity refinement network; and obtaining a refined disparity map output by the disparity refinement network by at least inputting an initial disparity map into the disparity refinement network, and fusing each image in the plurality of images and the feature map output by the corresponding layer structure, wherein the initial disparity map is generated at least based on the target view.
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公开(公告)号：US20220172376A1
公开(公告)日：2022-06-02
申请号：US17675979
申请日：2022-02-18
Inventor： Xiangbo SU , Jian WANG , Hao SUN
Abstract: The present disclosure provides a target tracking method, a target tracking device and an electronic apparatus. The target tracking method includes: inputting an ith image and an (i−1)th image in a to-be-detected video stream into a target deep learning model, i being an integer greater than 1; detecting a target in the ith image to obtain a first target detection box, and tracking the target in the (i−1)th image to obtain a tracking heatmap; and determining a target tracking result in accordance with the first target detection box, the tracking heatmap and the (i−1)th image.
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公开(公告)号：US20220027639A1
公开(公告)日：2022-01-27
申请号：US17494682
申请日：2021-10-05
Inventor： Yingying LI , Xiao TAN , Hao SUN
Abstract: A lane line detection method, an electronic device, and a storage medium, related to the field of artificial intelligence, and particularly related to computer vision and deep learning technologies, which can be applied to intelligent traffic scenes, are provided. The method includes: dividing an image into a foreground region and a background region; determining a solid line and a dotted line included in the foreground region; determining, according to the solid line and the dotted line comprised in the foreground region, whether a dotted-and-solid line is included in the foreground region; and determining a lane line detection result according to the solid line, the dotted line, and whether a dotted-and-solid line is comprised in the foreground region. According to the technical solution, the accuracy of lane line detection can be improved.
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40.发明申请公开(公告)号：US20210287015A1
公开(公告)日：2021-09-16
申请号：US17336641
申请日：2021-06-02
Inventor： Minyue JIANG , Xiao TAN , Hao SUN
Abstract: The present application discloses a method and an apparatus for vehicle re-identification, a training method, an electronic device and a storage medium, relating to the field of artificial intelligence, in particular, to technologies of computer vision, deep learning and intelligent transport. A specific implementation is: acquiring a picture of a target vehicle to be re-identified, determining a target two-dimensional image of the target vehicle based on the picture and a preset initial three-dimensional model, the initial three-dimensional model being generated based on sample three-dimensional information of a sample vehicle, and re-identifying the target two-dimensional image to generate and output an identification result.
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