Beijing Didi Infinity Technology and Development Co., Ltd.

Runbo Hu

Hua Chai

Pengfei Xu

Bin Xu

Jun Zhang

Zhiwei Ruan

Xiaoqiang Teng

Guangzhi Wang

Ronghao Li

Yaxian Li

Zhichao Song

Sicheng Zhao

Ling Bao

Yang Gu

Xiance Du

Shanghang Zhang

Huanqing Zhou

The embodiments of the present disclosure provide a visual positioning method, the method may include obtaining a positioning image collected by an imaging device; obtaining a three-dimensional (3D) point cloud map associated with an area where the imaging device is located; determining a target area associated with the positioning image from the 3D point cloud map based on the positioning image; and determining positioning information of the imaging device based on the positioning image and the target area.

Systems and methods for visual positioning

Embodiments of the disclosure provide systems and methods for domain adaptation between a plurality of source domains and a target domain. The artificial intelligence method includes receiving labeled data from the plurality of source domains and unlabeled data from the target domain. The method further includes separately training, by a processor, a plurality of source classifiers each corresponding to a source domain using the labeled data received from the respective source domains. The method also includes selecting a subset of the labeled data received from each source domain based on a similarity between the selected labeled data and the unlabeled data of the target domain. The method additionally includes refining, by the processor, each source classifier using the selected subset of the labeled data, and predicting labels of the unlabeled data using the refined source classifiers.

Machine learning systems and methods with source-target adaptation

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Beijing, China

Runbo Hu