FSOCO: The Formula Student Objects in Context Dataset

Published in arXiv preprint, 2020

Recommended citation: D. Dodel, M. Schötz, and N. Vödisch. "FSOCO: The Formula Student Objects in Context Dataset", arXiv preprint arXiv:2012.07139, Dec 2020. https://arxiv.org/pdf/2012.07139.pdf

This paper presents the FSOCO dataset, a collaborative dataset for vision-based cone detection systems in Formula Student Driverless competitions. It contains human annotated ground truth labels for both bounding boxes and instance-wise segmentation masks. The data buy-in philosophy of FSOCO asks student teams to contribute to the database first before being granted access ensuring continuous growth. By providing clear labeling guidelines and tools for a sophisticated raw image selection, new annotations are guaranteed to meet the desired quality. The effectiveness of the approach is shown by comparing prediction results of a network trained on FSOCO and its unregulated predecessor.

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