Abstract: An image generation method includes the following steps. Illumination lamps on a target object in an original image are detected; the original image is converted into an image to be processed that is in a specific scene; in the image to be processed, at least one illumination lamp of which operation state does not match scene information of the specific scene is determined as an object to be replaced; a replacement image including the object to be replaced of which operation state matches the scene information is determined according to the scene information and the object to be replaced; and the image in a region occupied by the object to be replaced in the image to be processed is replaced with the replacement image to generate a target image.

Abstract: An image generation method includes: an original image is converted into an image to be processed under a specific scenario; in the image to be processed, a region to be adjusted of which image rendering state does not match scenario information of the specific scenario is determined; the image rendering state of the region to be adjusted is related to light illuminated on a target object in the original image, and the target object includes a vehicle; a target rendering state in the region to be adjusted is determined; the target rendering state matches the scenario information; and in the image to be processed, the image rendering state of the region to be adjusted is adjusted to the target rendering state, to obtain a target image.

Abstract: Method and apparatus for generating a road map, electronic device, and non-transitory computer storage medium are disclosed, including: inputting a remote sensing image into a first neural network to extract first road feature information of multiple channels via the first neural network; inputting the first road feature information of multiple channels into a third neural network, to extract third road feature information of multiple channels via the third neural network, where the third neural network is a neural network trained by using road direction information as supervision information; fusing the first road feature information and the third road feature information; and generating a road map according to a fusion result.

Abstract: Methods, apparatuses, electronic devices, and computer readable storage media for image processing are provided. In one aspect, an image processing method includes: determining a plurality of image feature maps of a target image, the plurality of image feature maps corresponding to different preset scales; determining, based on the plurality of image feature maps and for each pixel of pixels in the target image, a first probability that the pixel in the target image belongs to a foreground and a second probability that the pixel in the target image belongs to a background; and performing panoramic segmentation on the target image based on the plurality of image feature maps, the first probabilities of the pixels in the target image, and the second probabilities of the pixels in the target image.

Abstract: Embodiments of the present disclosure disclose a lane line-based intelligent driving control method and apparatus, and an electronic device. The method includes: obtaining a lane line detection result of a vehicle traveling environment; determining, according to a traveling state of the vehicle and the lane line detection result, an estimated distance of traveling out of the lane line by the vehicle and/or estimated time of traveling out of the lane line by the vehicle; and performing intelligent driving control on the vehicle according to the estimated distance and/or the estimated time. The embodiments of the present disclosure implement lane line-based intelligent control on the vehicle traveling state, thereby helping to improve the driving safety.

Abstract: The present disclosure provides a method, an apparatuses and a storage medium for processing an image. According to an example of the method, n times of feature extraction are performed on the to-be-processed image, to obtain a pixel feature recognition result. Each time of feature extraction includes p data nodes, in each time of feature extraction, data on each data node except the last data node is determined based on data obtained by processing data on each of the data nodes before the data node respectively via a preset feature extraction method in that time of feature extraction and input data of that time of feature extraction. A feature extraction method used in each time of feature extraction includes feature extraction methods used for data on the data nodes in that time of feature extraction. Thereafter, the to-be-processed image can be processed based on the pixel feature recognition result.

Abstract: Lane line attribute detection methods and apparatuses, electronic devices, and intelligent devices are provided.

Abstract: An intelligent driving control method and apparatus, and a computer storage medium are provided The method includes: obtaining a pavement image of a pavement on which a vehicle travels; determining a category of a pavement scene in the pavement image according to the obtained pavement image; and performing an intelligent driving control on the vehicle according to the determined category of the pavement scene.

Abstract: Embodiments of the present disclosure disclose a lane line-based intelligent driving control method and apparatus, and an electronic device. The method includes: obtaining a lane line detection result of a vehicle traveling environment; determining, according to a traveling state of the vehicle and the lane line detection result, an estimated distance of traveling out of the lane line by the vehicle and/or estimated time of traveling out of the lane line by the vehicle; and performing intelligent driving control on the vehicle according to the estimated distance and/or the estimated time. The embodiments of the present disclosure implement lane line-based intelligent control on the vehicle traveling state, thereby helping to improve the driving safety.

Abstract: An intelligent driving control method, an electronic device, and a medium are provided. The method comprises: obtaining a lane line detection result of a running environment of a vehicle; determining, according to a running state of the vehicle and the lane line detection result, an estimated distance at which the vehicle drives out of a lane line; in response to the estimated distance being greater than a first preset distance value and less than or equal to a second preset distance value, determining an estimated time after which the vehicle drives out of the lane line; and performing intelligent driving control according to the estimated time.

Abstract: Method and apparatus for generating a road map, electronic device, and non-transitory computer storage medium are disclosed, including: inputting a remote sensing image into a first neural network to extract first road feature information of multiple channels via the first neural network; inputting the first road feature information of multiple channels into a third neural network, to extract third road feature information of multiple channels via the third neural network, where the third neural network is a neural network trained by using road direction information as supervision information; fusing the first road feature information and the third road feature information; and generating a road map according to a fusion result.

Abstract: The disclosure provides a positioning service method and system, and a terminal. In the above method, a positioned terminal receives a movement track model established by a positioning service platform; the positioned terminal judges whether or not positioning data that are collected satisfy the movement track model; and when the positioning data satisfy the movement track model, it is determined that there is no need to report the positioning data, and when the positioning data do not satisfy the movement track model, the positioning data are reported to the positioning service platform. The technical solution provided by the disclosure can reduce the frequency for the positioned terminal to report the positioning data and also save network data traffic for the user.

Abstract: The disclosure provides a positioning service method and system, and a terminal. In the above method, a positioned terminal receives a movement track model established by a positioning service platform; the positioned terminal judges whether or not positioning data that are collected satisfy the movement track model; and when the positioning data satisfy the movement track model, it is determined that there is no need to report the positioning data, and when the positioning data do not satisfy the movement track model, the positioning data are reported to the positioning service platform. The technical solution provided by the disclosure can reduce the frequency for the positioned terminal to report the positioning data and also save network data traffic for the user.