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 …

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

Fusing LiDAR and camera information is essential for accurate and reliable 3D object
detection in autonomous driving systems. This is challenging due to the difficulty of …

3D object detection is an important task that has been widely applied in autonomous driving.
Recently, fusing multi-modal inputs, ie, LiDAR and camera data, to perform this task has …

Enhancing original LiDAR point cloud features with virtual points has gained widespread
attention in multimodal information fusion. However, existing methods struggle to leverage …

LiDAR and camera are two common sensors to collect data in time for 3D object detection
under the autonomous driving context. Though the complementary information across …

3D object detection from LiDAR data for autonomous driving has been making remarkable
strides in recent years. Among the state-of-the-art methodologies, encoding point clouds into …

Integrating LiDAR and Camera information into Bird's-Eye-View (BEV) has become an
essential topic for 3D object detection in autonomous driving. Existing methods mostly adopt …

Integrating LiDAR and camera information into Bird's-Eye-View (BEV) representation has
emerged as a crucial aspect of 3D object detection in autonomous driving. However …

Camera and LIDAR are both important sensor modalities for real-world applications,
especially autonomous driving. The sensors provide complementary information and make …