We present the HIT-UAV dataset, a high-altitude infrared thermal dataset for object detection applications on Unmanned Aerial Vehicles (UAVs). The dataset comprises 2,898 infrared thermal images extracted from 43,470 frames in hundreds of videos captured by UAVs in various scenarios including schools, parking lots, roads, and playgrounds. Moreover, the HIT-UAV provides essential flight data for each image, such as flight altitude, camera perspective, date, and daylight intensity. For each image, we have manually annotated object instances with bounding boxes of two types (oriented and standard) to tackle the challenge of significant overlap of object instances in aerial images. To the best of our knowledge, the HIT-UAV is the first publicly available high-altitude UAV-based infrared thermal dataset for detecting persons and vehicles. We have trained and evaluated well-established object detection algorithms on the HIT-UAV. Our results demonstrate that the detection algorithms perform exceptionally well on the HIT-UAV compared to visual light datasets since infrared thermal images do not contain significant irrelevant information about objects. We believe that the HIT-UAV will contribute to various UAV-based applications and researches. The dataset is freely available at https://github.com/suojiashun/HIT-UAV-Infrared-Thermal-Dataset.

翻译：我们提出了HIT-UAV数据集，这是一个用于无人机（UAV）目标检测任务的高空红外热成像数据集。该数据集包含从数百段无人机视频中的43,470帧里提取的2,898张红外热图像，这些视频拍摄于学校、停车场、道路和操场等多种场景。此外，HIT-UAV还为每张图像提供了关键飞行数据，如飞行高度、相机视角、日期和日光强度。针对每张图像，我们手工标注了两种类型（有向框和标准框）的边界框作为目标实例，以解决航拍图像中目标实例严重重叠的难题。据我们所知，HIT-UAV是首个公开可用的基于高空无人机平台、用于人员和车辆检测的红外热成像数据集。我们已在HIT-UAV上训练并评估了多种成熟的检测算法。结果表明，由于红外热图像不包含大量与目标无关的显著信息，检测算法在HIT-UAV上的性能优于可见光数据集。我们相信HIT-UAV将为各类基于无人机的应用和研究做出贡献。该数据集可在https://github.com/suojiashun/HIT-UAV-Infrared-Thermal-Dataset 免费获取。