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  • N. Vödisch
  • D. Dodel
  • Michael Schötz

FSOCO: The Formula Student Objects in Context Dataset

In: SAE International Journal of Connected and Automated Vehicles vol. 5

  • (2022)

DOI: 10.4271/12-05-01-0003

This article presents the Formula Student Objects in Context (FSOCO) dataset, a collaborative dataset for vision-based cone detection systems in Formula Student Driverless (FSD) 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 the prediction results of a network trained on FSOCO and its unregulated predecessor. The FSOCO dataset can be found at fsoco-dataset.com.
  • TC Plattling MoMo