BirdsEyeView: Aerial View Dataset for Object Classification and Detection
Yunlong Qi, Dong Wang, Junfei Xie, Kejie Lu, Yan Wan, Shengli Fu · 2019
In recent years, deep learning based computer vision technology has progressed rapidly thanks to the significant increases in computing power and high-quality datasets. In this article, we present an aerial view image and video dataset dedicated to facilitating vision applications on the UAV platform, such as object detection, classification and tracking. The dataset consists of 5,000 images, each of which is carefully annotated according to the guidelines of the PASCAL VOC. The dataset is designed to cover diverse real-life scenes with aerial view angles which is different from other datasets. Such kind of specific dataset will be of great importance in developing and testing deep learning algorithms for UAV applications. Moreover, the dataset can serve as a benchmark to evaluate UAV visual solutions.