Abstract: A computer-implemented method for annotating driving scenario sensor data, including the steps of receiving raw sensor data, the raw sensor data comprising a plurality of successive LIDAR point clouds and/or a plurality of successive camera images, recognizing objects in each image of the camera data and/or each point cloud using one or more neural networks, correlating objects within successive images and/or point clouds, removing false positive results on the basis of plausibility criteria, and exporting the annotated sensor data of the driving scenario.

Abstract: A computer-implemented method for automatically annotating frames of sensor data includes: receiving the frames of sensor data; grouping the frames into a plurality of packets based on at least one condition attribute, wherein the at least one condition attribute describes at least one environment condition that existed while a respective frame of sensor data was being recorded; annotating frames from a first packet using a neural network, wherein the annotating comprises assigning at least one data point to each frame, wherein the first packet comprises frames for which the at least one condition attribute is in a selected value range; selecting a first sample of one or more frames from the first packet and determining a quality measure for data points of the first sample; and ascertaining that the quality measure for the first sample is below a predefined threshold.