We focus on the task of far-field 3D detection (Far3Det) of objects beyond a certain distance from an observer, e.g., $>$50m. Far3Det is particularly important for autonomous vehicles (AVs) operating at highway speeds, which require detections of far-field obstacles to ensure sufficient braking distances. However, contemporary AV benchmarks such as nuScenes underemphasize this problem because they evaluate performance only up to a certain distance (50m). One reason is that obtaining far-field 3D annotations is difficult, particularly for lidar sensors that produce very few point returns for far-away objects. Indeed, we find that almost 50% of far-field objects (beyond 50m) contain zero lidar points. Secondly, current metrics for 3D detection employ a "one-size-fits-all" philosophy, using the same tolerance thresholds for near and far objects, inconsistent with tolerances for both human vision and stereo disparities. Both factors lead to an incomplete analysis of the Far3Det task. For example, while conventional wisdom tells us that high-resolution RGB sensors should be vital for 3D detection of far-away objects, lidar-based methods still rank higher compared to RGB counterparts on the current benchmark leaderboards. As a first step towards a Far3Det benchmark, we develop a method to find well-annotated scenes from the nuScenes dataset and derive a well-annotated far-field validation set. We also propose a Far3Det evaluation protocol and explore various 3D detection methods for Far3Det. Our result convincingly justifies the long-held conventional wisdom that high-resolution RGB improves 3D detection in the far-field. We further propose a simple yet effective method that fuses detections from RGB and lidar detectors based on non-maximum suppression, which remarkably outperforms state-of-the-art 3D detectors in the far-field.
翻译:我们的重点是远方3D探测器(Far3Det)对距离观察者一定距离以外的物体进行远方3D探测(far3Det)的任务,例如5 000美元。Far3Det对于以高速公路速度运行的自主车辆(AVs)特别重要,这需要探测远方障碍以确保足够的制动距离。然而,当代AV基准,如NuScenes, 低估了这一问题,因为它们只评价到一定距离(50米)的性能。一个原因是,获得远方3D说明是困难的,特别是利达尔传感器,这些传感器为远方物体带来很少的点回报。事实上,我们发现近50%的远方3DD(超过50米)物体含有零利差点点。第二,目前3D(远方)探测器使用“一刀切的通用”哲学,使用与近方和远方物体相同的容忍阈值阈值门槛,这与人类视力和立体3D的容忍度差异不相符。两种因素导致对FAR3D任务的分析不完全。例如常规智慧告诉我们,高分辨率评估RGB3的RGB传感器应该比远方3远方3远方标准,而远方3FD探测器探测器探测器探测器探测器探测器的测测程测程测程,一个远方的测程方法应该显示远方。