Constructing a virtual world for the Metaverse based on real-world data is crucial, yet
creating virtual environments for crowded scenes poses challenges in accurately tracking …

On-device adapting to continual, unpredictable domain shifts is essential for mobile
applications like autonomous driving and augmented reality to deliver seamless user …

Autonomous vehicles and human drivers are prone to line-of-sight limitations. Road-side
mounted 3D sensors like LiDARs can augment a vehicle's on-board perception. However …

The Internet of Vehicles (IoV) has become a fundamental platform for advancing Intelligent
Transportation Systems (ITSs) and Intelligent Connected Vehicles (ICVs). However, the …

Multimodal sensing systems are increasingly prevalent in various real-world applications.
Most existing multimodal learning approaches heavily rely on training with a large amount of …

Recent works have considered two qualitatively different approaches to overcome line-of-
sight limitations of 3D sensors used for perception: cooperative perception and infrastructure …

LiDAR (Light Detection and Ranging) has been widely used in autonomous driving to
perceive the surrounding environment of self-driving cars. Advanced LiDAR perception …

Vehicular Metaverses are developed to enhance the modern automotive industry with an
immersive and safe experience among connected vehicles and roadside infrastructures, eg …

Vehicle-road cooperative perception plays an important role in intelligent transportation
systems. By receiving cooperative perception messages (CPM) shared from the roadside …

The registration of LiDAR point clouds between Connected Vehicles (CV s) is the basis for
vision tasks such as multi-vehicle cooperative perception and high-precision scene …