RaLiBEV: Radar and LiDAR BEV Fusion Learning for Anchor Box Free Object Detection Systems

In autonomous driving, LiDAR and radar are crucial for environmental perception. LiDAR offers precise 3D spatial sensing information but struggles in adverse weather like fog. Conversely, radar signals can penetrate rain or mist due to their specific wavelength but are prone to noise disturbances. Recent state-of-the-art works reveal that the fusion of radar and LiDAR can lead to robust detection in adverse weather. The existing works adopt convolutional neural network architecture to extract features from each sensor data, then align …

anchor art autonomous autonomous driving box cs.ai cs.cv cs.lg detection driving environmental free fusion information lidar noise perception radar rain sensing spatial state systems weather