Pillar-based 3D object detection methods outperform traditional point-based and voxel-
based methods in terms of speed. However, most of recent methods in this category use …

Cooperatively utilizing both ego-vehicle and infrastructure sensor data can significantly
enhance autonomous driving perception abilities. However, the uncertain temporal …

LiDAR and camera are two essential sensors for 3D object detection in autonomous driving.
LiDAR provides accurate and reliable 3D geometry information while the camera provides …

This thesis focuses on advancing the state-of-the-art 3D object detection and localization in
autonomous driving. An autonomous vehicle requires operating within a very unpredictable …

We introduce the Precise Synthetic Image and LiDAR (PreSIL) dataset for autonomous
vehicle perception. Grand Theft Auto V (GTA V), a commercial video game, has a large …

Three-dimensional object detection is vital for understanding the autonomous vehicle
driving environment. Different sensors are used for this purpose, such as cameras and …

Autonomous driving perception relies on standard sensors such as color cameras and
LiDAR, but each sensor has limitations when sensing complex and diverse environments …

In complex traffic environment scenarios, it is very important for autonomous vehicles to
accurately perceive the dynamic information of other vehicles around the vehicle in …

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 …

Abstract 3D object detection from the LiDAR point cloud plays an important role in
autonomous driving. It is difficult to balance inference speed and detection accuracy when …