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

Real-time 3D Object Detection using Feature Map Flow