公开(公告)号：US20230206595A1

公开(公告)日：2023-06-29

申请号：US18085264

申请日：2022-12-20

Applicant: Beijing Baidu Netcom Science Technology Co., Ltd.

Inventor： Fuqiang Liu ,  Zhongqiang Cai ,  Yu Guo ,  Yan Chen ,  Ji Wan ,  Jun Wang ,  Liang Wang ,  Huimin Ma

IPC: G06V10/75 ,  G06V10/774 ,  G06V20/58 ,  G06V20/64

CPC classification number: G06V10/753 ,  G06V10/774 ,  G06V20/58 ,  G06V20/647 ,  G06V2201/07

Abstract: A three-dimensional data augmentation method includes that an original two-dimensional image and truth value annotation data matching the original two-dimensional image are acquired, that the original two-dimensional image and two-dimensional truth value annotation data are transformed according to a target transformation element to obtain a transformed two-dimensional image and transformed two-dimensional truth value annotation data, that an original intrinsic matrix is transformed according to the target transformation element to obtain a transformed intrinsic matrix, that a two-dimensional projection is performed on three-dimensional truth value annotation data according to the transformed intrinsic matrix to obtain projected truth value annotation data, and that three-dimensional augmentation image data is generated according to the transformed two-dimensional image, the transformed two-dimensional truth value annotation data, and the projected truth value annotation data.

公开(公告)号：US20250117602A1

公开(公告)日：2025-04-10

申请号：US18988044

申请日：2024-12-19

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

Inventor： Zhaoxu Wang ,  Qiang Xie ,  Yuhang Zheng ,  Shouke Qin ,  Zonggang Wu ,  Yuanhua Shao ,  Yan Wang ,  Ruohan Chang ,  Qingqing Wu ,  Lu Wang ,  Songge Guo ,  Chang Li ,  Xi Cao ,  Qian Wu ,  Xiaoyu Hu ,  Huijie Liu ,  Yu Guo ,  Hui Xue ,  Rufeng Cheng

IPC: G06F40/40

Abstract: A large model-based recommendation method includes: determining description information of interested content corresponding to a target user; inputting a content to be recommended, the description information of interested content and current popular search sentences into a large model to generate at least one recommendation card corresponding to the content to be recommended, in which the recommendation card contains a recommendation word associated with the content to be recommended; obtaining a current behavior characteristic of the target user; and in response to the current behavior characteristic satisfying a display condition of the recommendation card, displaying the recommendation card corresponding to at least one content to be recommended.