  In this paper, we present a real-time 3D detection approach considering
time-spatial feature map aggregation from different time steps of deep neural
model inference (named feature map flow, FMF). Proposed approach improves the
quality of 3D detection center-based baseline and provides real-time
performance on the nuScenes and Waymo benchmark. Code is available at
https://github.com/YoushaaMurhij/FMFNet
