四川轻化工大学学报（自然科学版）2025，Vol.38Issue(4)：48-57,10.DOI:10.11863/j.suse.2025.04.06
基于多模态融合的3D目标检测技术研究
Research on 3D Object Detection Technology Based on Multimodal Fusion
摘要
Abstract
Aiming at the problem of missed detection of long-distance targets in the field of autonomous driving,an improved 3D target detection model based on CenterFusion is proposed,which combines camera and millimeter wave radar data.First of all,the early fusion strategy is introduced to map the radar data to the image plane and combine it with the image data to form multi-channel input to enhance the anti-jamming ability of the network model.Secondly,after the feature fusion network,the attention mechanism is introduced to make the model focus on the key information extraction of the fusion feature map,which effectively improves the accuracy of 3D target detection.Then,the loss function is further improved to solve the problem of imbalance between positive and negative samples.Finally,the proposed model is used to carry out comparative experiments and ablation experiments on nuScenes data sets,and the results show that the average detection accuracy of the improved model is 1.5%higher than that of the traditional CenterFusion model,and the NuScenes detection score of the improved model is 2.1%higher,effectively improving the detection ability of long-distance targets.关键词
自动驾驶/传感器融合/3D目标检测/早期融合/注意力机制Key words
autonomous driving/sensor fusion/3D target detection/early fusion/attention mechanism分类
信息技术与安全科学引用本文复制引用
曾恒,姚娅川..基于多模态融合的3D目标检测技术研究[J].四川轻化工大学学报（自然科学版）,2025,38(4):48-57,10.基金项目
四川省科技厅重大专题项目(2018GZDZX0045) （2018GZDZX0045）
