ArtifiVe-Potsdam - A Benchmark for Learning with Artificial Objects for Improved Aerial Vehicle Detection.

In order to enable the development of powerful machine learning methods for remote sensing-based Earth observation tasks, benchmarks are needed to evaluate the methods and compare them to other methods comprehensively. We present ArtifiVe-Potsdam, a freely available dataset that is targeting vehicle detection in aerial imagery. In particular, the benchmark focuses on enriching real datasets with artificial data and quantifying the added value. The dataset aims to stimulate research on the efficient and cost-effective creation and enrichment of datasets for remote sensing since datasets with a limited number of labels are common and the collection of data and labels is time-consuming and expensive.