Konferenzbeitrag
Instance-level augmentation for synthetic agricultural data using depth maps
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Date
2023
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Publisher
Gesellschaft für Informatik e.V.
Abstract
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.