Map Annotation

Map annotation, crucial for creating high-definition (HD) maps used in autonomous driving, focuses on efficiently and accurately labeling map elements like roads, poles, and traffic signals within images and point cloud data. Current research emphasizes developing automated annotation systems, often employing vision-centric approaches and deep learning models (e.g., transformers, convolutional neural networks) to reduce reliance on manual labeling, which is time-consuming and expensive. These advancements improve the speed and accuracy of HD map creation, directly impacting the development and safety of autonomous vehicles and other location-based services.