Large receptive field strategy and important feature extraction strategy in 3D object detection

arXiv:2401.11913v2 Announce Type: replace
Abstract: The enhancement of 3D object detection is pivotal for precise environmental perception and improved task execution capabilities in autonomous driving. LiDAR point clouds, offering accurate depth information, serve as a crucial information for this purpose. Our study focuses on key challenges in 3D target detection. To tackle the challenge of expanding the receptive field of a 3D convolutional kernel, we introduce the Dynamic Feature Fusion Module (DFFM). This module achieves adaptive expansion of the 3D …

3d object 3d object detection abstract arxiv autonomous autonomous driving capabilities challenges cs.ai cs.cv detection driving environmental extraction feature feature extraction information key lidar object perception pivotal serve strategy study type