A ground mark determining method, performed by a computer device, the method comprising: obtaining, by the computer device, a point cloud grayscale image, the point cloud grayscale image comprising a road segment map, wherein the obtaining the point cloud grayscale image comprises: obtaining, by the computer device, a three-dimensional laser point cloud map; and performing, by the computer device, a coordinate transformation according to a yaw of a vehicle based on the three-dimensional laser point cloud map, performing an orthographic projection on the transformed three-dimensional laser point cloud map, and normalizing reflectance values of laser points in the three-dimensional laser point cloud map into grayscale values, to obtain a two-dimensional point cloud grayscale image; obtaining, by the computer device, ground mark information from the road segment map by running a mark-extraction network model extracting ground marks in the road segment map, the ground mark information comprising information about the ground marks extracted by the mark-extraction network model, and the ground marks indicating driving information marked on a road segment surface, where the ground marks include one or more of arrows, texts, digits or patterns, and wherein the obtaining ground mark information from the road segment map by running a mark-extraction network model extracting ground marks in the road segment map comprises: dividing the road segment map into a plurality of road segment sub-maps by running the mark-extraction network model; performing, by the computer device, a convolution and a pooling on each of the plurality of road segment sub-maps, to obtain a plurality of feature maps corresponding to each of the plurality of road segment sub-maps; and extracting, by the computer device, the ground mark information in the plurality of feature maps corresponding to each of the road segment sub-maps; and determining, by the computer device, a target ground mark from the ground marks according to the ground mark information. obtaining, by the computer device, a point cloud grayscale image, the point cloud grayscale image comprising a road segment map, wherein the obtaining the point cloud grayscale image comprises: obtaining, by the computer device, a three-dimensional laser point cloud map; and performing, by the computer device, a coordinate transformation according to a yaw of a vehicle based on the three-dimensional laser point cloud map, performing an orthographic projection on the transformed three-dimensional laser point cloud map, and normalizing reflectance values of laser points in the three-dimensional laser point cloud map into grayscale values, to obtain a two-dimensional point cloud grayscale image; obtaining, by the computer device, a three-dimensional laser point cloud map; and performing, by the computer device, a coordinate transformation according to a yaw of a vehicle based on the three-dimensional laser point cloud map, performing an orthographic projection on the transformed three-dimensional laser point cloud map, and normalizing reflectance values of laser points in the three-dimensional laser point cloud map into grayscale values, to obtain a two-dimensional point cloud grayscale image; obtaining, by the computer device, ground mark information from the road segment map by running a mark-extraction network model extracting ground marks in the road segment map, the ground mark information comprising information about the ground marks extracted by the mark-extraction network model, and the ground marks indicating driving information marked on a road segment surface, where the ground marks include one or more of arrows, texts, digits or patterns, and wherein the obtaining ground mark information from the road segment map by running a mark-extraction network model extracting ground marks in the road segment map comprises: dividing the road segment map into a plurality of road segment sub-maps by running the mark-extraction network model; performing, by the computer device, a convolution and a pooling on each of the plurality of road segment sub-maps, to obtain a plurality of feature maps corresponding to each of the plurality of road segment sub-maps; and extracting, by the computer device, the ground mark information in the plurality of feature maps corresponding to each of the road segment sub-maps; and dividing the road segment map into a plurality of road segment sub-maps by running the mark-extraction network model; performing, by the computer device, a convolution and a pooling on each of the plurality of road segment sub-maps, to obtain a plurality of feature maps corresponding to each of the plurality of road segment sub-maps; and extracting, by the computer device, the ground mark information in the plurality of feature maps corresponding to each of the road segment sub-maps; and determining, by the computer device, a target ground mark from the ground marks according to the ground mark information.