Multimodal fusion technology significantly enhances the safety and perception capabilities
of intelligent vehicles. Recently, replacing Cartesian coordinate system voxels with polar …

Sensor fusion is crucial for an accurate and robust perception system on autonomous
vehicles. Most existing datasets and perception solutions focus on fusing cameras and …

Perception plays a vital role in autonomous driving as it serves as a prerequisite for
downstream planning and decision tasks. The existing research has mainly focused on …

Autonomous vehicles rely extensively on onboard sensors to perceive their surrounding
environments for motion planning and vehicle control. Despite recent advancements …

Multi-modal sensor fusion techniques have promoted the development of autonomous
driving, while perception in the complex environment remains a challenging problem. In …

As a critical component to realizing widespread autonomous driving, 3D perception systems
have come to be heavily studied in the community. However, many solutions are solely …

Achieving robust and real-time 3D perception is fundamental for autonomous vehicles.
While most existing 3D perception methods prioritize detection accuracy, they often overlook …

The fusion of multi-modal perception in autonomous driving plays a pivotal role in vehicle
behavior decision-making. However, much of the previous research has predominantly …

Cooperative perception in the field of connected autonomous vehicles (CAVs) aims to
overcome the inherent limitations of single-vehicle perception systems, including long-range …

The pursuit of autonomous driving relies on developing perception systems capable of
making accurate, robust, and rapid decisions to interpret the driving environment effectively …