Beijing Baidu Netcom Science Technology Co., Ltd

Beijing Baidu Netcom Science and Technology Co., Ltd.

Xipeng Yang

Hao Sun

Xiao Tan

Errui Ding

Shilei Wen

Hongwu Zhang

Minyue Jiang

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.

Method for training image depth estimation model and method for processing image depth information

Embodiments of the present disclosure disclose a method and apparatus for determining a target anchor, a device and a storage medium. The method may include: extracting a plurality of feature maps of an original image using a feature extraction network; inputting the plurality of feature maps into a feature pyramid network to perform feature fusion, to obtain a plurality of fused feature maps; and using a region proposal network to implement operations as follows: determining an initial anchor of a network head using the fused feature map, based on a size of each fused feature map, and determining an offset parameter of the initial anchor, based on a ratio of the size of the fused feature map to the original image, and generating a plurality of candidate anchors in different directions, based on the offset parameter of the initial anchor.

Method and apparatus for determining target anchor, device and storage medium

Embodiments of the present disclosure provide an object tracking method and an apparatus. The method includes: obtaining multiple frames of first images shot by a first camera apparatus and a first shooting moment of each frame of the first images, where the first images include a first object; obtaining multiple frames of second images shot by a second camera apparatus and a second shooting moment of each frame of the second images, where the second images include a second object; obtaining a distance between the first camera apparatus and the second camera apparatus; and judging whether the first object and the second object are the same object according to the multiple frames of the first images, the first shooting moment of each frame of the first images, the multiple frames of the second images, the second shooting moment of each frame of the second images and the distance.

Object tracking method and apparatus

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Beijing, China

Xipeng Yang