Wübben, HenningButz, Raphaelavon Szadkowski, KaiBarenkamp, MarcoHoffmann, ChristaStein, AnthonyRuckelshausen, ArnoMüller, HenningSteckel, ThiloFloto, Helga2023-02-212023-02-212023978-3-88579-724-1https://dl.gi.de/handle/20.500.12116/40258Image augmentation is a key component in computer vision pipelines. Its techniques utilize different levels of data annotation. A lack of methods can be observed when it comes to data that supplies depth maps, in particular synthetic data. We propose a novel augmentation method named DepthAug that utilizes depth annotations in image data and examine its performance in the context of object detection tasks. Results show a boost in MAP score performance compared to previous related methods.enimage augmentationsynthetic datadeep image compositingobject detectiondomain gapText/Conference Paper1617-5468