公开(公告)号：US20230419610A1

公开(公告)日：2023-12-28

申请号：US18185359

申请日：2023-03-16

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

Inventor： Xing LIU ,  Ruizhi CHEN ,  Yan ZHANG ,  Chen ZHAO ,  Hao SUN ,  Jingtuo LIU ,  Errui DING ,  Tian WU ,  Haifeng WANG

IPC: G06T17/20 ,  G06T5/50 ,  G06V10/26 ,  G06V10/60

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.

公开(公告)号：US20230289402A1

公开(公告)日：2023-09-14

申请号：US18055393

申请日：2022-11-14

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

Inventor： Jian WANG ,  Xiangbo SU ,  Qiman WU ,  Zhigang WANG ,  Hao SUN ,  Errui DING ,  Jingdong WANG ,  Tian WU ,  Haifeng WANG

IPC: G06K9/62

CPC classification number: G06K9/62 ,  G06K9/6288

Abstract: Provided are a joint perception model training method, a joint perception method, a device, and a storage medium. The joint perception model training method includes: acquiring sample images and perception tags of the sample images; acquiring a preset joint perception model, where the joint perception model includes a feature extraction network and a joint perception network; performing feature extraction on the sample images through the feature extraction network to obtain target sample features; performing joint perception through the joint perception network according to the target sample features to obtain perception prediction results; and training the preset joint perception model according to the perception prediction results and the perception tags, where the joint perception includes executing at least two perception tasks.

公开(公告)号：US20230185702A1

公开(公告)日：2023-06-15

申请号：US17856091

申请日：2022-07-01

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

Inventor： Tian WU ,  Yanjun MA ,  Dianhai YU ,  Yehua YANG ,  Yuning DU

IPC: G06F11/36 ,  G06N3/08

CPC classification number: G06F11/3688 ,  G06N3/08

Abstract: A method and apparatus is provided for generating and applying a deep learning model based on a deep learning framework, and relates to the field of computers. A specific implementation solution includes that a basic operating environment is established on a target device, where the basic operating environment is used for providing environment preparation for an overall generation process of a deep learning model; a basic function of the deep learning model is generated in the basic operating environment according to at least one of a service requirement and a hardware requirement, to obtain a first processing result; an extended function of the deep learning model is generated in the basic operating environment based on the first processing result, to obtain a second processing result; and a preset test script is used to perform function test on the second processing result, to output a test result.

公开(公告)号：US20220004526A1

公开(公告)日：2022-01-06

申请号：US17480294

申请日：2021-09-21

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

Inventor： Liujie ZHANG ,  Yamei LI ,  Huihuang ZHENG ,  Hongyu LIU ,  Xiang LAN ,  Dianhai YU ,  Yanjun MA ,  Tian WU ,  Haifeng WANG

IPC: G06F16/21 ,  G06F16/22

Abstract: According to exemplary embodiments of the present disclosure, there is provided a method and apparatus of converting a schema in a deep learning framework, and a computer storage medium. The method of converting the schema in the deep learning framework includes: updating a first schema, based on first syntax elements in the first schema and a context relationship between the first syntax elements in the first schema, so as to obtain an updated first schema; generating second syntax elements corresponding to updated first syntax elements in the updated first schema, based on a mapping relationship between the updated first syntax elements in the updated first schema and second syntax elements in a second schema system; and combining the second syntax elements according to a context relationship between the updated first syntax elements, so as to generate a second schema