Autonomous driving has been among the most popular and challenging topics in the past
few years. Among all modules in autonomous driving, High-definition (HD) map has drawn …

Autonomous driving has been among the most popular and challenging topics in the past
few years. On the road to achieving full autonomy, researchers have utilized various …

Remote sensing images are useful for a wide variety of planet monitoring applications, from
tracking deforestation to tackling illegal fishing. The Earth is extremely diverse---the amount …

A comprehensive representation of an image requires understanding objects and their
mutual relationship, especially in image-to-graph generation, eg, road network extraction …

We propose SAM-Road an adaptation of the Segment Anything Model (SAM) for extracting
large-scale vectorized road network graphs from satellite imagery. To predict graph …

Road network graphs provide critical information for autonomous-vehicle applications, such
as drivable areas that can be used for motion planning algorithms. To find road network …

Online lane graph construction is a promising but challenging task in autonomous driving.
Previous methods usually model the lane graph at the pixel or piece level, and recover the …

Vectorized high-definition (HD) maps contain detailed information about surrounding road
elements, which are crucial for various downstream tasks in modern autonomous driving …

Digital maps with lane-level details are the foundation of many applications. However,
creating and maintaining digital maps especially maps with lane-level details, are labor …

The task of road extraction has aroused remarkable attention due to its critical role in
facilitating urban development and up-to-date map maintenance, which has widespread …