This competition is designed to push the state-of-the-art in object detection with drone platform forward. Teams are required to predict the bounding boxes of objects of nine predefined classes (i.e., people, bicycle, motor, pickup, car, van, truck, bus and boat) with real-valued confidences. Some rarely occurring special vehicles (e.g., machineshop truck, forklift truck, and tanker) are ignored in evaluation.
The challenge containing 10,349 static images (8,078 for training and 2,271 for testing) captured by drone platforms in different places at different heights, are available on the download page. We manually annotate the bounding boxes of different categories of objects in each image. Annotations on the training sets are publicly available.
The object detection evaluation page lists detailed information regarding how submissions will be scored. To limit overfitting while providing researchers more flexibility to test their algorithms, we have divided the test set into two splits, including test-challenge and test-dev.