生成鸟瞰图感知数据的合成工具，支持多传感器与多任务
SimBEV: A Synthetic Multi-Task Multi-Sensor Driving Data Generation Tool and Dataset
- 用可配置的合成数据生成器模拟真实驾驶场景
- 产出包含鸟瞰图分割与3D目标检测标注的大规模数据集
- 适合自动驾驶感知算法研发者使用
近年来，鸟瞰图（BEV）感知在自动驾驶领域受到广泛关注，因其有助于多模态传感器融合。然而，现有数据集对BEV表示支持不足，构建新数据集耗时费力。为此，我们提出SimBEV——一种高度可配置、可扩展的随机合成数据生成工具，支持多种传感器，整合多源信息以生成精确的BEV真值，并支持包括BEV分割和3D目标检测在内的多种感知任务。利用SimBEV构建了大规模标注数据集SimBEV，涵盖多样化驾驶场景。该工具与数据集均公开可用。
原文摘要 · Abstract (English)
Bird's-eye view (BEV) perception has garnered significant attention in autonomous driving in recent years, in part because BEV representation facilitates multi-modal sensor fusion. BEV representation enables a variety of perception tasks including BEV segmentation, a concise view of the environment useful for planning a vehicle's trajectory. However, this representation is not fully supported by existing datasets, and creation of new datasets for this purpose can be a time-consuming endeavor. To address this challenge, we introduce SimBEV. SimBEV is a randomized synthetic data generation tool that is extensively configurable and scalable, supports a wide array of sensors, incorporates information from multiple sources to capture accurate BEV ground truth, and enables a variety of perception tasks including BEV segmentation and 3D object detection. SimBEV is used to create the SimBEV dataset, a large collection of annotated perception data from diverse driving scenarios. SimBEV and the SimBEV dataset are open and available to the public.
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