公开(公告)号：US20200349389A1

公开(公告)日：2020-11-05

申请号：US16828845

申请日：2020-03-24

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

Inventor： Jiadong ZHANG ,  Chao LI ,  Guoyi LIU

IPC: G06K9/62 ,  G06K9/46 ,  G06T7/73

Abstract: The present disclosure relates to a method and a device for training an image recognition model and a related device. The method includes: extracting sub-image feature data from a detection frame sub-image of an input image; determining element feature data matching the sub-image feature data from an index element database; and outputting images related to the element feature data as training images for training the image recognition model. The index element database is built in advance based on a plurality of element feature data extracted from a plurality of candidate images.

公开(公告)号：US20210090266A1

公开(公告)日：2021-03-25

申请号：US16926238

申请日：2020-07-10

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

Inventor： Kai WEI ,  Yuning DU ,  Chenxia LI ,  Guoyi LIU

IPC: G06T7/187 ,  G06T7/136 ,  G06T7/174 ,  G06T7/00 ,  G06K9/46

Abstract: Embodiments of the present disclosure provide a method and device for labelling a point of interest, a computer device, and a storage medium. The method includes the following. Image data to be labelled is obtained. The image data includes an image to be labelled and a collection location of the image to be labelled. Feature extraction is performed on the image to be labelled to obtain a first image feature of the image to be labelled. A first reference image corresponding to the image to be labelled is determined based on a similarity between the first image feature and a second image feature corresponding to each reference image in an image library. The point of interest of the image to be labelled is labelled based on a category of the first reference image and the collection location of the image to be labelled.