-
公开(公告)号：US20230102467A1
公开(公告)日：2023-03-30
申请号：US17956393
申请日：2022-09-29
IPC: G06V10/25 , G06V10/44 , G06V10/764 , G06V10/771 , G06V10/82
Abstract: A method of detecting an image, an electronic device, and a storage medium are provided, which relate to a field of an artificial intelligence technology, in particular to fields of computer vision and deep learning technologies, and may be applied to a smart city and an intelligent cloud. The method includes: performing a feature extraction on an image to be detected, so as to obtain a feature map of the image to be detected; generating a prediction box in the feature map according to the feature map; generating a mask for the prediction box according to a key region of a target object; and classifying the prediction box using the mask as a classification enhancement information, so as to obtain a category of the prediction box.
-
公开(公告)号：US20230027813A1
公开(公告)日：2023-01-26
申请号：US17936570
申请日：2022-09-29
Inventor： Xipeng YANG , Xiao TAN , Hao SUN , Errui DING
Abstract: An object detecting method includes: obtaining an object image of an object; obtaining an object feature map by performing feature extraction on the object image; obtaining decoded features by performing feature mapping on the object feature map by adopting a mapping network of an object recognition model; obtaining positions of prediction boxes by inputting the decoded features into a first prediction layer of the object recognition model to perform object regression prediction; and obtaining classes of objects within the prediction boxes by inputting the decoded features into a second prediction layer of the object recognition model to perform object class prediction.
-
13.发明申请公开(公告)号：US20230005272A1
公开(公告)日：2023-01-05
申请号：US17944742
申请日：2022-09-14
Inventor： Yingying LI , Xiao TAN , Hao SUN
Abstract: The present disclosure provides a method and apparatus for detecting a traffic anomaly, a device, a storage medium and a computer program product, relates to the field of artificial intelligence, and specifically to computer vision and deep learning technologies, and can be applied to intelligent transportation scenarios. A specific implementation of the method comprises: acquiring a traffic video stream; performing vehicle detection tracking on the traffic video stream to determine whether there is an abnormally stopped vehicle, wherein a stop with a time length exceeding a preset time length belongs to an abnormal stop; and performing a traffic anomaly classification on a video frame corresponding to the abnormal stop using a decision tree to obtain a traffic anomaly type, if there is the abnormally stopped vehicle, wherein the decision tree is generated based on features for a traffic anomaly detection.
-
公开(公告)号：US20220392204A1
公开(公告)日：2022-12-08
申请号：US17891381
申请日：2022-08-19
IPC: G06V10/774 , G06V10/776
Abstract: A method of training a model, an electronic device, and a readable storage medium are provided, which relate to a field of artificial intelligence, in particular to computer vision and deep learning technologies, and specifically used in smart city and intelligent transportation scenarios. The method includes: determining a target pre-trained model; and performing an unsupervised training and/or a semi-supervised training on the target pre-trained model based on an image acquired by the target terminal, so as to obtain a first target trained model.
-
15.发明申请公开(公告)号：US20220375118A1
公开(公告)日：2022-11-24
申请号：US17880931
申请日：2022-08-04
Inventor： Yingying LI , Xinyi DAI , Xiao TAN , Hao SUN
Abstract: Provided is a method and apparatus for identifying a vehicle cross-line. The method may include: determining, in each road condition image of a plurality of road condition images, position information of a target lane line and position information of a target vehicle; determining, based on the position information of the target lane line and the position information of the target vehicle, a relative positional relationship between the target vehicle and the target lane line corresponding to the each road condition image; and determining that the target vehicle crosses the line, if the relative positional relationships corresponding to the plurality of road condition images meet a preset condition.
-
Patent Agency Ranking
公开(公告)号：US20220027651A1
公开(公告)日：2022-01-27
申请号：US17450261
申请日：2021-10-07
Abstract: A method for generating a license plate defacement classification model, a license plate defacement classification method an electronic device and a storage medium, and related to the technical field of artificial intelligence, and specifically, to the technical field of computer vision and the technical field of intelligent transportation are provided. The method for generating a license plate defacement classification model includes: acquiring training data, wherein the training data includes a plurality of annotated vehicle images, annotated content includes information indicating that a license plate is defaced or is not defaced, and the annotated content further includes location information of a license plate area; and training a first neural network by using the training data, to obtain the license plate defacement classification model for predicting whether the license plate in a target vehicle image is defaced. A robust license plate defacement classification model can be obtained by using embodiments.
-
17.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.
-
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.
-
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.
-
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.
-
-
-
-
-
-
-
-
-
Search Results
23
records
(took 0.018 seconds)
