Oktoberfest Food Dataset

Oktoberfest Food Dataset

Alexander Ziller, Julius Hansjakob, Vitalii Rusinov, Daniel Zügner, Peter Vogel, Stephan Günnemann

We release a realistic, diverse, and challenging dataset for object detection on images. The data was recorded at a beer tent in Germany and consists of 15 different categories of food and drink items. We created more than 2,500 object annotations by hand for 1,110 images captured by a video camera above the checkout. We further make available the remaining 600GB of (unlabeled) data containing days of footage. Additionally, we provide our trained models as a benchmark. Possible applications include automated checkout systems which could significantly speed up the process.

paper: https://arxiv.org/pdf/1912.05007.pdf
dataset: GitHub - a1302z/OktoberfestFoodDataset: Publication of our Oktoberfest Food Dataset for Object Detection methods

Citation

@misc{tum2019oktoberfest,
    title={Oktoberfest Food Dataset},
    author={Alexander Ziller and Julius Hansjakob and Vitalii Rusinov and Daniel Z\"ugner and Peter Vogel and Stephan G\"unnemann},
    year={2019},
    eprint={1912.05007},
    archivePrefix={arXiv},
    primaryClass={cs.CV}
}
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