Once an academic venture, autonomous driving has received unparalleled corporate funding in the last decade. Still, operating conditions of current autonomous cars are mostly restricted to ideal scenarios. This means that driving in challenging illumination conditions such as night, sunrise, and sunset remains an open problem. In these cases, standard cameras are being pushed to their limits in terms of low light and high dynamic range performance. To address these challenges, we propose, DSEC, a new dataset that contains such demanding illumination conditions and provides a rich set of sensory data. DSEC offers data from a wide-baseline stereo setup of two color frame cameras and two high-resolution monochrome event cameras. In addition, we collect lidar data and RTK GPS measurements, both hardware synchronized with all camera data. One of the distinctive features of this dataset is the inclusion of high-resolution event cameras. Event cameras have received increasing attention for their high temporal resolution and high dynamic range performance. However, due to their novelty, event camera datasets in driving scenarios are rare. This work presents the first high resolution, large scale stereo dataset with event cameras. The dataset contains 53 sequences collected by driving in a variety of illumination conditions and provides ground truth disparity for the development and evaluation of event-based stereo algorithms.

中文翻译：

---

DSEC：用于驾驶场景的立体声事件摄像机数据集

过去十年来，自动驾驶曾经是一门学术型企业，它获得了无与伦比的公司资金。尽管如此，当前无人驾驶汽车的运行条件大多仅限于理想情况。这意味着在充满挑战的照明条件下（例如夜晚，日出和日落）驾驶仍然是一个悬而未决的问题。在这些情况下，标准相机在低照度和高动态范围性能方面被推到了极限。为了应对这些挑战，我们建议DSEC，一个新的数据集，其中包含这种苛刻的照明条件，并提供了丰富的感官数据集。DSEC提供了从宽基线的立体声设置中获取的数据，该立体声设置包括两个彩色框架摄像机和两个高分辨率的单色事件摄像机。此外，我们收集激光雷达数据和RTK GPS测量值，这两种硬件均与所有相机数据同步。该数据集的显着特征之一是包含高分辨率事件摄像机。事件摄像机因其高时间分辨率和高动态范围性能而受到越来越多的关注。但是，由于其新颖性，驾驶场景中的事件摄像机数据集很少见。这项工作展示了第一个带有事件摄像机的高分辨率，大规模立体声数据集。该数据集包含在各种照明条件下驾驶收集的53个序列，并为基于事件的立体声算法的开发和评估提供了地面真相差异。驾驶场景中的事件摄像机数据集很少见。这项工作展示了第一个带有事件摄像机的高分辨率，大规模立体声数据集。该数据集包含在各种照明条件下驾驶收集的53个序列，并为基于事件的立体声算法的开发和评估提供了地面真相差异。驾驶场景中的事件摄像机数据集很少见。这项工作展示了第一个带有事件摄像机的高分辨率，大规模立体声数据集。该数据集包含在各种照明条件下驾驶收集的53个序列，并为基于事件的立体声算法的开发和评估提供了地面真相差异。