用低功耗芯片实现实时3D车检，精度仅比高端显卡低0.2%。
Real-Time 3D Object Detection Using InnovizOne LiDAR and Low-Power Hailo-8 AI Accelerator
- 在Hailo-8芯片上部署PointPillars模型，实现5Hz实时推理。
- 使用InnovizOne LiDAR获得高质量点云，远距离检测效果更优。
- 低功耗硬件达成接近高端显卡的精度，适合量产落地。
3D目标检测是自动驾驶的关键技术。尽管摄像头与激光雷达（LiDAR）广泛用于该任务，但传统方法如PointPillars通常依赖高功耗硬件。多数旋转式LiDAR存在点云稀疏问题，难以保证车辆前方的检测质量。本文研究基于InnovizOne LiDAR生成的3D点云，在低功耗Hailo-8 AI加速器上实现实时3D目标检测。InnovizOne传感器相比传统旋转式方案能提供更高分辨率的点云，尤其在远距离检测中表现更佳。实验表明，系统可在约5Hz帧率下完成实时推理，达到0.91%的F1分数，仅比运行于NVIDIA GeForce RTX 2080 Ti的同一模型下降0.2%。该成果证明，低成本、低功耗硬件可实现高效3D目标检测，推动自动驾驶技术向更普及方向发展。源代码与预训练模型已开源。
原文摘要 · Abstract (English)
Object detection is a significant field in autonomous driving. Popular sensors for this task include cameras and LiDAR sensors. LiDAR sensors offer several advantages, such as insensitivity to light changes, like in a dark setting and the ability to provide 3D information in the form of point clouds, which include the ranges of objects. However, 3D detection methods, such as PointPillars, typically require high-power hardware. Additionally, most common spinning LiDARs are sparse and may not achieve the desired quality of object detection in front of the car. In this paper, we present the feasibility of performing real-time 3D object detection of cars using 3D point clouds from a LiDAR sensor, processed and deployed on a low-power Hailo-8 AI accelerator. The LiDAR sensor used in this study is the InnovizOne sensor, which captures objects in higher quality compared to spinning LiDAR techniques, especially for distant objects. We successfully achieved real-time inference at a rate of approximately 5Hz with a high accuracy of 0.91% F1 score, with only -0.2% degradation compared to running the same model on an NVIDIA GeForce RTX 2080 Ti. This work demonstrates that effective real-time 3D object detection can be achieved on low-cost, low-power hardware, representing a significant step towards more accessible autonomous driving technologies. The source code and the pre-trained models are available at https://github.com/AIROTAU/ PointPillarsHailoInnoviz/tree/main
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