Abstract: A processor-implemented method including embedding sensing information, from a plurality of sensors, at a current time point with a previous path of a vehicle at a previous time point and topology information for a topology including plural nodes at the previous time point, determining, by inputting the embedded sensing information to a topology-based neural network, a first distribution area and a second distribution area within a search area, where the first distribution area includes a determined feasible path and the second distribution area includes disconnected nodes that are determined to be reconnected or rewired due to an obstacle, and generating a current path at the current time point from a target location of the vehicle to a current position of the vehicle using topology information at the current time point determined based on the determining.

Abstract: A processor-implemented method including determining, from a first image frame, a first amodal region including a visible region in which a static landmark is visible and an occluded region in which the static landmark is occluded, calculating an occluded region confidence information for the occluded region in the first amodal region based on the first amodal region, determining a second amodal region corresponding to the static landmark from a second image frame temporally subsequent to the first image frame, calculating transformation information between the first image frame and the second image frame based on the first amodal region, the second amodal region, and the occluded region confidence information, and calculating localization information of an electronic device comprising the processor based on the transformation information.

Abstract: A method and apparatus for calibrating a camera are provided. The method and apparatus include obtaining a driving image captured by a camera mounted on a vehicle, segmenting line regions including straight lines from the captured driving image, extracting feature points of the straight lines from the line regions, projecting the feature points of the straight lines into a world coordinate system, and estimating an error for a calibration parameter of the camera including at least one of a pitch, a roll, or a yaw so that the feature points projected into the world coordinate system satisfy a line parallel condition.

Abstract: A processor-implemented method with lane line determination includes: determining, from an input image, road feature information comprising a surrounding object and a road surface marking comprising a lane line; matching the road feature information to lane lines of a driving road on which a vehicle is driving; detecting whether there is a change in a road structure based on a result of the matching, wherein the change in the road structure comprises any one or any combination of any two or more of a change of the lane line, a loss of the lane line, and a change of a road sign; and based on whether the change in the road structure is detected, determining lane line information of the driving road by using information on the surrounding object.

Abstract: An apparatus and method with data labeling are provided. An apparatus includes one or more processors configured to obtain localization information related to an object, based on the localization information, extract a landmark point from a landmark map including coordinates of a landmark, generate a ground truth image based on the extracted landmark point, and generate training data by refining the ground truth image.

Abstract: To estimate a position of a moving object, an electronic device generate two-dimensional (2D) feature point information of a landmark-based probability map from the surrounding image, obtain landmark-based three-dimensional (3D) feature point information from the HD map data, convert one of the 2D feature point information of the surrounding image to 3D or the 3D feature point information of the HD map data to 2D, determine a similarity between the converted feature point information and one of the feature point information of the surrounding image and the feature point information of the HD map data that is not converted, and estimate a position of the moving object based on the similarity.

Abstract: A method with distance estimation includes detecting a pedestrian region of a pedestrian comprised in a plurality of images received from a camera; determining a static point in the detected pedestrian region; and determining a distance between the pedestrian and the camera based on the static point in each of the images and a position of the camera corresponding to each of the images.