xView: Objects in Context in Overhead Imagery
This dataset advances object detection research in overhead imagery, addressing the need for high-resolution and diverse public data in this domain.
The authors introduced xView, a large-scale satellite imagery dataset for object detection, containing over 1 million objects across 60 classes in over 1,400 km² of imagery, and provided a baseline analysis using the Single Shot MultiBox Detector.
We introduce a new large-scale dataset for the advancement of object detection techniques and overhead object detection research. This satellite imagery dataset enables research progress pertaining to four key computer vision frontiers. We utilize a novel process for geospatial category detection and bounding box annotation with three stages of quality control. Our data is collected from WorldView-3 satellites at 0.3m ground sample distance, providing higher resolution imagery than most public satellite imagery datasets. We compare xView to other object detection datasets in both natural and overhead imagery domains and then provide a baseline analysis using the Single Shot MultiBox Detector. xView is one of the largest and most diverse publicly available object-detection datasets to date, with over 1 million objects across 60 classes in over 1,400 km^2 of imagery.