AI RESEARCH
FALO: Fast and Accurate LiDAR 3D Object Detection on Resource-Constrained Devices
arXiv CS.CV
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ArXi:2506.04499v2 Announce Type: replace Existing LiDAR 3D object detection methods predominantely rely on sparse convolutions and/or transformers, which can be challenging to run on resource-constrained edge devices, due to irregular memory access patterns and high computational costs. In this paper, we propose FALO, a hardware-friendly approach to LiDAR 3D detection, which offers both state-of-the-art (SOTA) detection accuracy and fast inference speed.