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公开(公告)号:US12147247B2
公开(公告)日:2024-11-19
申请号:US17884136
申请日:2022-08-09
Inventor: Haodong Ding , Liangjun Zhang
IPC: G05D1/00
Abstract: Provided are a vehicle attitude estimation method, an electronic device and a storage medium, relates to a technical field of data processing, and in particular to fields of automatic driving, intelligent transportation, Internet of Things, big data and the like. A specific implementation solution includes: obtaining first target data, based on point cloud data of a vehicle, the first target data being capable of constituting a target surface of the vehicle; performing attitude estimation on a target body for surrounding the vehicle, based on the first target data, to obtain an estimation result; and estimating an attitude of the vehicle, based on the estimation result. According to the implementation solution, precise or accurate estimation of the attitude of the vehicle may be achieved.
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公开(公告)号:US12125224B2
公开(公告)日:2024-10-22
申请号:US17564626
申请日:2021-12-29
Inventor: Xibin Song , Liangjun Zhang
CPC classification number: G06T7/55 , G06V20/58 , G06V20/588 , G06T2207/10028
Abstract: Provided are a depth information processing method, an apparatus, and a storage medium, which relate to the field of image processing and, in particular, to computer vision, deep learning and autonomous driving. A specific implementation includes: determining intermediate depth information of a target scene according to sparse depth information of the target scene by a sub-model unit in a depth information supplementing model; and using intermediate depth information determined by a tail sub-model unit in the depth information supplementing model as dense depth information of the target scene.
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公开(公告)号:US20220122281A1
公开(公告)日:2022-04-21
申请号:US17564626
申请日:2021-12-29
Inventor: Xibin Song , Liangjun Zhang
Abstract: Provided are a depth information processing method, an apparatus, and a storage medium, which relate to the field of image processing and, in particular, to computer vision, deep learning and autonomous driving. A specific implementation includes: determining intermediate depth information of a target scene according to sparse depth information of the target scene by a sub-model unit in a depth information supplementing model; and using intermediate depth information determined by a tail sub-model unit in the depth information supplementing model as dense depth information of the target scene.
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