Baidu USA LLC

Beijing Baidu Netcom Science and Technology Co., Ltd.

Baidu Online Network Technology (beijing) Co., Ltd.

Baidu.com Times Technology (beijing) Co. Ltd.

Dingfu Zhou

Ruigang Yang

Liangjun Zhang

Jin Fang

Xibin Song

Zhibin Hong

Feixiang Lu

Yanfu Zhang

Sibo Zhang

Miao Liao

The present application provides a model training method and apparatus, and a prediction method and apparatus, and it relates to fields of artificial intelligence, deep learning, image processing, and autonomous driving. The model training method includes: inputting a first sample image of sample images into a depth information prediction model, and acquiring depth information of the first sample image; acquiring inter-image posture information based on a second sample image of the sample images and the first sample image; acquiring a projection image corresponding to the first sample image, at least according to the inter-image posture information and the depth information; and acquiring a loss function by determining a function for calculating a similarity between the second sample image and the projection image, and training the depth information prediction model using the loss function.

Model training method and apparatus, and prediction method and apparatus

A radar point cloud data processing method and device, an apparatus, and storage medium are provided, which are related to technical fields of radar point cloud, automatic driving, and deep learning. An implementation includes: determining a target location area where a target object is located by utilizing a target detection box in the radar point cloud data; removing each point of the target object in the target location area from the radar point cloud data; and adding an object model to the target location area. By applying embodiments of the present disclosure, richer radar point cloud data may be obtained by removing the target object from the radar point cloud data and adding the needed three-dimensional model to the target location area in the radar point cloud data.

Radar point cloud data processing method and device, apparatus, and storage medium

Systems and methods of video inpainting for autonomous driving are disclosed. For example, the method stitches a multiplicity of depth frames into a 3D map, where one or more objects in the depth frames have previously been removed. The method further projects the 3D map onto a first image frame to generate a corresponding depth map, where the first image frame includes a target inpainting region. For each target pixel within the target inpainting region of the first image frame, based on the corresponding depth map, the method further maps the target pixel within the target inpainting region of the first image frame to a candidate pixel in a second image frame. The method further determines a candidate color to fill the target pixel. The method further performs Poisson image editing on the first image frame to achieve color consistency at a boundary and between inside and outside of the target inpainting region of the first image frame. For each pixel in the target inpainting region of the first image frame, the method further traces the pixel into neighboring frames and replacing an original color of the pixel with an average of colors sampled from the neighboring frames.

Depth-guided video inpainting for autonomous driving

Embodiments of the present disclosure disclose a method and apparatus for recognizing a face. A specific embodiment of the method includes: acquiring at least two facial images of a to-be-recognized face under different illuminations using a near-infrared photographing device; generating at least one difference image based on a brightness difference between each two of the at least two facial images; determining a facial contour image of the to-be-recognized, face based on the at least one difference image; inputting the at least two facial images, the at least one difference image, and the facial contour image into a pre-trained real face prediction value calculation model to obtain a real face prediction value of the to-be-recognized face; and outputting prompt information for indicating successful recognition of a real face, in response to determining the obtained real face prediction value being greater than a preset threshold.

Method and apparatus for recognizing face

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Beijing, China

Dingfu Zhou