RPEA: A Residual Path Network with Efficient Attention for 3D pedestrian detection from LiDAR point clouds

Jinzheng Guang, Zhengxi Hu, Shichao Wu, Qianyi Zhang, Jingtai Liu

Abstract: Highlights•We present an end-to-end trainable single-stage 3D pedestrian detection network.•To retain spatial information lost during downsampling and suppress point cloud noise.•The method ranks first on the JRDB 3D object detection leaderboard.•The method has higher accuracy and faster inference speeds.•The proposed approach can be better deployed to vehicles and mobile robots.