公开(公告)号：US11694436B2

公开(公告)日：2023-07-04

申请号：US17164681

申请日：2021-02-01

Applicant: BEIJING BAIDU NETCOM SCIENCE TECHNOLOGY CO., LTD.

Inventor： Minyue Jiang ,  Xiao Tan ,  Hao Sun ,  Hongwu Zhang ,  Shilei Wen ,  Errui Ding

IPC: G06T7/00 ,  G06V20/56 ,  G06V20/10 ,  G06V20/20 ,  G06N3/045

CPC classification number: G06V20/20 ,  G06N3/045 ,  G06T7/97 ,  G06V20/176 ,  G06V20/56

Abstract: The present application discloses a vehicle re-identification method and apparatus, a device and a storage medium, which relates to the field of computer vision, intelligent search, deep learning and intelligent transportation. The specific implementation scheme is: receiving a re-identification request from a terminal device, the re-identification request including a first image of a first vehicle shot by a first camera and information of the first camera; acquiring a first feature of the first vehicle and a first head orientation of the first vehicle according to the first image; determining a second image of the first vehicle from images of multiple vehicles according to the first feature, multiple second features extracted based on the images of the multiple vehicles in an image database, the first head orientation of the first vehicle, and the information of the first camera; and transmitting the second image to the terminal device.

公开(公告)号：US12169942B2

公开(公告)日：2024-12-17

申请号：US17324174

申请日：2021-05-19

Applicant: BEIJING BAIDU NETCOM SCIENCE TECHNOLOGY CO., LTD.

Inventor： Minyue Jiang ,  Xipeng Yang ,  Xiao Tan ,  Hao Sun

IPC: G06T7/00 ,  G06T7/55 ,  G06T7/13 ,  B60W60/00 ,  G01S13/89 ,  G01S13/931 ,  G06N3/08

Abstract: A method for training an image depth estimation model. A sample environmental image, sample environmental point cloud data and sample edge information of the sample environmental image are input into a to-be-trained model; 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 are determined through the to-be-trained model, the initial depth information of each of the pixel points is optimized according to the feature relationship to obtain optimized depth information of each of the pixel points, and a parameter of the to-be-trained model is adjusted according to the optimized depth information to obtain the image depth estimation model.