In this paper we apply the deformable part model by Felzenszwalb et al., which is at this moment the state of the art in many computer vision related tasks, to detect different types of man made structures in very high resolution aerial images - a reputedly difficult problem in our field. We test the framework on a database of crops of aerial images at a definition of 10 cm/pixel and investigate how the model performs on several classes of objects. The results show that the model can achieve reasonable performance in this context. However, depending on the type of object, there are specific issues which will have to be taken into account to build an effective semi-supervised annotation tool based on this model.