Konferenzbeitrag
Instance-level augmentation for synthetic agricultural data using depth maps
Vorschaubild nicht verfügbar
Volltext URI
Dokumententyp
Text/Conference Paper
Zusatzinformation
Datum
2023
Zeitschriftentitel
ISSN der Zeitschrift
Bandtitel
Verlag
Gesellschaft für Informatik e.V.
Zusammenfassung
Image 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.