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公开(公告)号：US20240013364A1
公开(公告)日：2024-01-11
申请号：US18003992
申请日：2022-01-29
Inventor： Xinyi DAI , Wei ZHANG , Xiaolin LIANG
IPC: G06T7/00
CPC classification number: G06T7/0002 , G06T2200/24 , G06T2207/20084 , G06T2207/20104
Abstract: An image-based vehicle damage assessment method includes: obtaining an image to be assessed of a damaged vehicle; outputting a first damage assessment box and first damage information based on the image to be assessed; in response to a first box selection operation on the image to be assessed, determining and outputting a second damage assessment box and second damage information corresponding to the first box selection operation, in which a vehicle damage image indicated by the second damage assessment box is different from the vehicle damage image indicated by the first damage assessment box, and the second damage information is vehicle damage information of the vehicle damage image indicated by the second damage assessment box.
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公开(公告)号：US20230419610A1
公开(公告)日：2023-12-28
申请号：US18185359
申请日：2023-03-16
Inventor： Xing LIU , Ruizhi CHEN , Yan ZHANG , Chen ZHAO , Hao SUN , Jingtuo LIU , Errui DING , Tian WU , Haifeng WANG
CPC classification number: G06T17/20 , G06T5/50 , G06V10/26 , G06V10/60 , G06T2207/10028 , G06T2207/20221
Abstract: An image rendering method includes the steps below. A model of an environmental object is rendered to obtain an image of the environmental object in a target perspective. An image of a target object in the target perspective and a model of the target object are determined according to a neural radiance field of the target object. The image of the target object is fused and rendered into the image of the environmental object according to the model of the target object.
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公开(公告)号：US20230419601A1
公开(公告)日：2023-12-28
申请号：US17989996
申请日：2022-11-18
Inventor： Sha Li , Yaqian Shen , Zhidong Yin , Zhixiang Chen
IPC: G06T17/00
CPC classification number: G06T17/00 , G06T2215/16 , G06T2210/12
Abstract: Provided is a method for adjusting a target object, an electronic device, and a storage medium, relating to a field of computer technology, and in particular, to fields of intelligent transportation, automatic driving, computer vision, and the like. The method includes: acquiring a first bounding box corresponding to the target object and a second bounding box corresponding to a support of the target object; obtaining an association relationship for adjustment of the target object, according to a spatial position where the first and second bounding boxes are located; and moving, according to the association relationship, the target object towards the support, to obtain a third bounding box corresponding to the adjusted target object, where the third bounding box and the second bounding box appear to fit each other.
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公开(公告)号：US20230401828A1
公开(公告)日：2023-12-14
申请号：US17905965
申请日：2022-04-08
Inventor： Meina QIAO , Shanshan LIU , Xiameng QIN , Chengquan ZHANG , Kun YAO
IPC: G06V10/774 , G06V30/14 , G06V10/764
CPC classification number: G06V10/774 , G06V10/764 , G06V30/1444
Abstract: A method for training an image recognition model includes: obtaining a training data set, in which the training data set includes first text images of each vertical category in a non-target scene and second text images of each vertical category in a target scene, and a type of text content involved in the first text images is the same as a type of text content involved in the second text image; training an initial recognition model by using the first text images, to obtain a basic recognition model; and modifying the basic recognition model by using the second text images, to obtain an image recognition model corresponding to the target scene.
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公开(公告)号：US20230401221A1
公开(公告)日：2023-12-14
申请号：US18063509
申请日：2022-12-08
Inventor： Lu GAN , Zenghui XU , Zhiqun XIA , Jianbing ZHANG , Lianghui CHEN , Jian GONG , Ke SUN
IPC: G06F16/2458 , G06F16/242 , G06F16/2453
CPC classification number: G06F16/2458 , G06F16/2433 , G06F16/24542
Abstract: Provided are a cross-tables search method, an electronic device and a storage medium, relating to a field of artificial intelligence, and in particular, to natural language processing, big data, knowledge graph technology, which may be applied in scenarios of smart cloud, smart city, and smart government affairs. The cross-tables search method includes: parsing a query to obtain an entity, attribute and relationship required to be searched; determining a cross-tables search strategy according to the entity, the attribute and the relationship; and performing a cross-tables search operation according to the cross-tables search strategy.
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Patent Agency Ranking
公开(公告)号：US11841446B2
公开(公告)日：2023-12-12
申请号：US17214630
申请日：2021-03-26
Inventor： Wenjie Liu , Renlan Cai , Xiaotao Li , Shiyu Song
Abstract: The present application discloses a positioning method and an apparatus, which relate to the technical field of intelligent driving. A specific implementation solution is: determining a first positioning result using point cloud data collected by lidar in combination with a laser point cloud reflection value map; constructing a constraint condition using the first positioning result, where the constraint condition is used to accelerate a convergence speed of solving a receiver position using observation data; performing GNSS-PPP positioning using the constraint condition in combination with observation data of a GNSS receiver to obtain a second positioning result. Using this solution, lidar positioning technology is combined with GNSS-PPP positioning technology to realize a purpose of not relying on a GNSS base station.
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377.发明授权公开(公告)号：US11836836B2
公开(公告)日：2023-12-05
申请号：US17527068
申请日：2021-11-15
Inventor： Shaoxiong Yang
Abstract: Methods and apparatuses for generating a model and generating a 3D animation, devices, and storage mediums are provided. The method for generating a model may include: acquiring a preset sample set; acquiring pre-established generative adversarial nets, the generative adversarial nets including a generator and a discriminator; and performing training steps as follows: selecting a sample from the sample set; extracting a sample audio feature from the sample audio of the sample; inputting the sample audio feature into the generator to obtain a pseudo 3D mesh vertex sequence of the sample; inputting the pseudo 3D mesh vertex sequence and the real 3D mesh vertex sequence of the sample into the discriminator to discriminate authenticity of 3D mesh vertices; and in response to determining that the generative adversarial nets meet a training completion condition, obtaining a trained generator as a model for generating a 3D animation.
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公开(公告)号：US11830236B2
公开(公告)日：2023-11-28
申请号：US17456367
申请日：2021-11-23
Inventor： Shaoxiong Yang
CPC classification number: G06V10/7515 , G06T11/00 , G06V10/242 , G06V10/32 , G06V10/50 , G06V40/161 , G06V40/171
Abstract: Provided are a method and a device for generating an avatar, an electronic equipment, a medium and a product. In the method, a to-be-detected face image of a current user is acquired. The to-be-detected face image is analyzed and at least one original component of the to-be-detected face image is obtained. Each original component of the at least one original component of the to-be-detected face image is matched with each candidate component in a component set corresponding to the each original component, and a target component corresponding to the each original component of the to-be-detected face image is obtained. The target component corresponding to the each original component of the to-be-detected face image is assembled into a personalized avatar of the current user.
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379.发明授权公开(公告)号：US11830207B2
公开(公告)日：2023-11-28
申请号：US17206999
申请日：2021-03-19
Inventor： Li Yu , Weixin Lu , Guowei Wan , Liang Peng , Shiyu Song
Abstract: A method, an electronic device and a readable storage medium for point cloud data processing, which may be used for autonomous driving, are disclosed. The feature vectors of respective points in the first point cloud data and second point cloud data are pre-learned, and thus the feature vectors of the first key points may be determined directly based on the learnt second feature vectors of respective first neighboring points of the respective first key points in the first point cloud data, and the feature vectors of the candidate key points may be determined directly based on the learnt third feature vectors of the respective second neighboring points of respective candidate key points in the second point cloud data corresponding to the first key points.
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公开(公告)号：US11829447B2
公开(公告)日：2023-11-28
申请号：US17173142
申请日：2021-02-10
Inventor： Xinjiang Lu , Nengjun Zhu , Hui Xiong
IPC: G06F17/18 , G06F18/2323 , G06N3/02 , G06F18/25
CPC classification number: G06F18/2323 , G06F17/18 , G06F18/25 , G06N3/02
Abstract: This disclosure discloses a resident area prediction method, apparatus, device and storage medium, involving artificial intelligence technology, big data, deep learning and multi-task learning. The specific implementation plan is: acquiring a resident area data of a target user, and the resident area data including the resident area of the target user and the corresponding resident time; obtaining an association relationship between the resident areas of the target user by inputting the resident area data into an area relationship model, and the area relationship model is used to reflect a position relationship between the areas; determining a time-sequence relationship between the areas visited by the target user, according to the association relationship, the resident time and the visiting POI data; predicting a target resident area of the target user, according to the time-sequence relationship and the basic attribute information of the target user.
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