MMFN: Multi-Modal-Fusion-Net for End-to-End Driving
Qingwen Zhang,Mingkai Tang,Ruoyu Geng,Feiyi Chen,Ren Xin,Lujia Wang,Qingwen Zhang,Mingkai Tang,Ruoyu Geng,Feiyi Chen,Ren Xin,Lujia Wang
Inspired by the fact that humans use diverse sensory organs to perceive the world, sensors with different modalities are deployed in end-to-end driving to obtain the global context of the 3D scene. In previous works, camera and LiDAR inputs are fused through transformers for better driving performance. These inputs are normally further interpreted as high-level map information to assist navigation...
