High-definition (HD) map provides abundant and precise static environmental information of
the driving scene, serving as a fundamental and indispensable component for planning in …

The aspiration of the next generation's autonomous driving (AD) technology relies on the
dedicated integration and interaction among intelligent perception, prediction, planning, and …

In recent years, the field of autonomous vehicles has seen a significant increase in
academic research, with high-definition (HD) maps emerging as a critical component of …

The recent development of online static map element (aka HD Map) construction algorithms
has raised a vast demand for data with ground truth annotations. However, available public …

In high-definition maps (HD maps), the road lane centerline and lane topology graph play
essential roles in navigation, planning, and decision-making. Existing research focusing on …

Online vector map construction based on visual data can bypass the processes of data
collection, post-processing, and manual annotation required by traditional map construction …

Generating annotations for bird's-eye-view (BEV) segmentation presents significant
challenges due to the scenes' complexity and the high manual annotation cost. In this work …

The recent development of online static map element (aka HD map) construction algorithms
has raised a vast demand for data with ground truth annotations. However, available public …

Highly accurate and robust vectorized reconstruction of road structures is crucial for
autonomous vehicles. Traditional LiDAR-based methods require multiple processes and are …

Vectorized reconstruction and topological cognition of road structures are crucial for
autonomous vehicles to handle complex scenes. Traditional frameworks rely heavily on high …