Abstract: Provided are a lane line recognition method, an electronic device and a storage medium, relating to a technical field of artificial intelligence, in particular to technical fields of intelligent transportation, automatic driving and deep learning. The lane line recognition method includes: extracting a basic feature of an original image; recognizing at least one lane line node in the original image by using the basic feature of the original image; extracting a local feature from the basic feature of the original image by using the at least one lane line node; fusing the basic feature and the local feature; and recognizing a lane line in the original image based on a fused result.

Abstract: Provided are a high-precision map construction method, an electronic device, and a storage medium, relating to the field of high-precision map technology and, in particular, to autonomous driving technology. The implementation solution includes: calculating a pose of a camera at each position point according to a pre-acquired video; calculating an absolute depth of each keypoint in the pre-acquired video according to the pose of the camera at each position point; constructing, according to the absolute depth of each keypoint in the video, a corresponding three-dimensional point cloud of each pixel point in the pre-acquired video; and constructing, according to the corresponding three-dimensional point cloud of each pixel point in the pre-acquired video, a high-precision map corresponding to the pre-acquired video.

Abstract: A method for detecting a road change is provided. The method includes: obtaining a road image comprising a road to be detected; extracting a road region in the road image as a target region, wherein the road region corresponds to where the road to be detected is located; obtaining a target geographical location of the target region; determining a reference region for the target region from pre-stored road regions based on the target geographical location; calculating a similarity between the target region and the reference region; and determining, based on the similarity, whether a passability of the road to be detected is changed. By applying the solution provided by the embodiments of the present disclosure, efficiency of road change detection can be improved.

Abstract: A method of rectifying a text image, a training method, an electronic device, and a medium, which relate to a field of an artificial intelligence technology, in particular to fields of computer vision, deep learning technology, intelligent transportation and high-precision maps. An exemplary implementation includes: performing, based on a gating strategy, a plurality of first layer-wise processing on a text image to be rectified, so as to obtain respective feature maps of a plurality of layer levels, wherein each of the feature maps includes a text structural feature related to the text image to be rectified, and the gating strategy is configured to increase an attention to the text structural feature; and performing a plurality of second layer-wise processing on the respective feature maps of the plurality of layer levels, so as to obtain a rectified text image corresponding to the text image to be rectified.

Abstract: Provided are a method and apparatus for correcting positioning information, an electronic device and a storage medium, which relate to the field of artificial intelligence, in particular, to intelligent transportation technology and image processing technology. The specific implementation solution includes steps described below. A to-be-corrected image and positioning information of the to-be-corrected image are acquired. A target candidate reference image matching the to-be-corrected image is selected from candidate reference images having accurate positioning information. The positioning information of the to-be-corrected image is corrected according to accurate positioning information of the target candidate reference image. According to the solution of the present disclosure, the positioning information of the to-be-corrected image can be quickly corrected, and a guarantee is provided for accurately updating a navigation map by using the to-be-corrected image subsequently.

Abstract: The present disclosure provides a method and apparatus for processing an image. A specific implementation includes: acquiring a top view of a road; identifying a position of a lane line from the top view; cutting the top view into at least two areas, and determining, according to the position of the lane line in each area, a width of a lane in the each area and an average width of the lane in the top view; calculating a first perspective correction matrix by optimizing a first loss function, the first loss function being used to represent a difference between the width of the lane in the each area and the average width of the lane in the top view; and performing a lateral correction on the top view through the first perspective correction matrix to obtain a first corrected image.

Abstract: A point cloud registration method, apparatus, device, and storage medium are provided. The method includes: acquiring target point cloud data; dividing the target point cloud data into a plurality of point cloud sets; determining a coincidence degree between every two point cloud sets and determining a fixed point cloud set and a registration point cloud set from two point cloud sets with a coincidence degree between the two point cloud sets being greater than a preset threshold; determining a target registration matrix between the fixed point cloud set and the registration point cloud set; and performing registration of the fixed point cloud set with the registration point cloud set according to the target registration matrix.

Abstract: The method for generating a road edge line includes: acquiring a road image; recognizing lane line information from the road image; recognizing key point information related to the road edge from the road image; and generating the road edge line according to the lane line information and the key point information.

Abstract: A road information processing method, an electronic device and a storage medium are provided, relates to the field of intelligent transportation, and may be used for the field of cloud computing or cloud. The method includes: acquiring a road image, and identifying a street lamp in the road image to obtain a street lamp identification result; associating the road image with an electronic map to obtain a road corresponding to the road image in the electronic map; and marking a street lamp attribute for the road corresponding to the road image in the electronic map based on the street lamp identification result.