HelixNet

HelixNet是由法国国家科学研究中心创建的大型LiDAR数据集，包含100亿个精细标注的3D点，涵盖6个法国城市的多样化场景。数据集通过组织点相对于传感器旋转，并记录其精确释放时间，以准确评估最先进的LiDAR序列分割算法的实时准备情况。HelixNet的应用领域主要集中在自动驾驶车辆的实时语义分割，旨在解决现有数据集在实时应用中存在的获取延迟问题。

HelixNet is a large-scale LiDAR dataset developed by the Centre National de la Recherche Scientifique (CNRS) of France. It contains 10 billion finely annotated 3D points, covering diverse scenarios across six French cities. By organizing the point cloud data relative to the sensor's rotational motion and recording the precise emission timestamps of each individual point, the dataset enables accurate evaluation of the real-time readiness of state-of-the-art LiDAR sequence segmentation algorithms. The primary application of HelixNet lies in real-time semantic segmentation for autonomous vehicles, aiming to address the acquisition latency issues of existing datasets in real-time applications.