基于高精度地图增强的三维目标检测算法

3D object detection based on high-precision map enhancement

将高精度地图信息融入主干检测网络中提出了基于高精度地图增强的三维目标检测算法(HME3D)。结合传统卷积和Transformer构建了新颖的地图特征提取模块(HFE)以实现地图特征的高效提取。此外,利用基于地图边缘增强的辅助监督网络(MEES)提升三维目标检测主任务的性能。最后,在具有挑战性的nuScenes数据集上验证了本文模型的优势,它相对纯点云基线模型精度提升了2.81 mAP。

A novel 3D object detection algorithm based on high-precision map enhancement(HME3D) was proposed by integrating high-precision map information into the backbone detection network.Specifically,the high-precision map feature extraction module(HFE) was constructed by combining traditional convolution and transformer to achieve efficient extraction of map features.In addition,the auxiliary supervision network(MEES) based on map edge enhancement was designed to improve the performance of the main 3D object detection task.Finally,the advantages of the proposed model in this paper are verified on the challenging nuScenes dataset,which improves the accuracy of the LiDAR baseline model by 2.81 mAP.