high altitude UAV multi-modal tracking dataset

The dataset consists of visible and infrared multimodal video captured by a drone equipped with a hybrid sensor at an altitude of 500 meters, mainly containing 150 visible and infrared video pairs, totaling more than 12,000 frame pairs. The dataset contains 9 target categories such as trucks and pedestrians, covering a variety of scenes (such as city, suburb, lake, construction site, viaduct, basketball court, lawn, plastic runway, residential area, square, street, etc.) and lighting conditions (day, night, fog, sunny, etc.), significantly increasing the diversity and challenge of the dataset. In addition to the 12 general tracking challenge attributes in the HiAl dataset, challenges specific to the drone perspective, such as drone rotation and small targets, were added. These challenge attributes comprehensively cover the complex scenarios and practical problems that may be encountered in high-altitude UAV target tracking missions. In order to ensure the high quality of the data set and the accuracy of the annotation, we carried out fine modal registration for the video of both visible and infrared modes, and manually labeled the target boundary boxes of all frames, adopting a unified modal annotation method to evaluate the performance of the multi-modal tracking method more accurately.