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  2. School of Engineering
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  4. Publikationen School of Engineering
Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-20647
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dc.contributor.authorTuggener, Lukas-
dc.contributor.authorSatyawan, Yvan Putra-
dc.contributor.authorPacha, Alexander-
dc.contributor.authorSchmidhuber, Jürgen-
dc.contributor.authorStadelmann, Thilo-
dc.date.accessioned2020-10-15T13:23:53Z-
dc.date.available2020-10-15T13:23:53Z-
dc.date.issued2021-
dc.identifier.isbn978-1-7281-8808-9de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/20647-
dc.descriptionThe dataset, code and pre-trained models, as well as user instructions, are publicly available at https://zenodo.org/record/4012193.de_CH
dc.description.abstractIn this paper, we present DeepScoresV2, an extended version of the DeepScores dataset for optical music recognition (OMR). We improve upon the original DeepScores dataset by providing much more detailed annotations, namely (a) annotations for 135 classes including fundamental symbols of non-fixed size and shape, increasing the number of annotated symbols by 23%; (b) oriented bounding boxes; (c) higher-level rhythm and pitch information (onset beat for all symbols and line position for noteheads); and (d) a compatibility mode for easy use in conjunction with the MUSCIMA++ dataset for OMR on handwritten documents. These additions open up the potential for future advancement in OMR research. Additionally, we release two state-of-the-art baselines for DeepScoresV2 based on Faster R-CNN and the Deep Watershed Detector. An analysis of the baselines shows that regular orthogonal bounding boxes are unsuitable for objects which are long, small, and potentially rotated, such as ties and beams, which demonstrates the need for detection algorithms that naturally incorporate object angles.de_CH
dc.language.isoende_CH
dc.publisherIEEEde_CH
dc.rightsLicence according to publishing contractde_CH
dc.subjectOptical music recognitionde_CH
dc.subjectDeep neural netde_CH
dc.subjectMusic object detectionde_CH
dc.subjectObject detectionde_CH
dc.subjectComputer visionde_CH
dc.subjectPattern recognitionde_CH
dc.subject.ddc006: Spezielle Computerverfahrende_CH
dc.titleThe DeepScoresV2 dataset and benchmark for music object detectionde_CH
dc.typeKonferenz: Paperde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Informatik (InIT)de_CH
dc.identifier.doi10.1109/ICPR48806.2021.9412290de_CH
dc.identifier.doi10.21256/zhaw-20647-
zhaw.conference.details25th International Conference on Pattern Recognition 2020 (ICPR’20), Online, 10-15 January 2021de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end9195de_CH
zhaw.pages.start9188de_CH
zhaw.publication.statusacceptedVersionde_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.title.proceedings2020 25th International Conference on Pattern Recognition (ICPR)de_CH
zhaw.webfeedDatalabde_CH
zhaw.webfeedInformation Engineeringde_CH
zhaw.webfeedZHAW digitalde_CH
zhaw.webfeedNatural Language Processingde_CH
zhaw.webfeedMachine Perception and Cognitionde_CH
zhaw.funding.zhawRealScore - Scanning of Real-World Sheet Music for a Digital Music Standde_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
zhaw.relation.referenceshttps://zenodo.org/record/4012193de_CH
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Tuggener, L., Satyawan, Y. P., Pacha, A., Schmidhuber, J., & Stadelmann, T. (2021). The DeepScoresV2 dataset and benchmark for music object detection [Conference paper]. 2020 25th International Conference on Pattern Recognition (ICPR), 9188–9195. https://doi.org/10.1109/ICPR48806.2021.9412290
Tuggener, L. et al. (2021) ‘The DeepScoresV2 dataset and benchmark for music object detection’, in 2020 25th International Conference on Pattern Recognition (ICPR). IEEE, pp. 9188–9195. Available at: https://doi.org/10.1109/ICPR48806.2021.9412290.
L. Tuggener, Y. P. Satyawan, A. Pacha, J. Schmidhuber, and T. Stadelmann, “The DeepScoresV2 dataset and benchmark for music object detection,” in 2020 25th International Conference on Pattern Recognition (ICPR), 2021, pp. 9188–9195. doi: 10.1109/ICPR48806.2021.9412290.
TUGGENER, Lukas, Yvan Putra SATYAWAN, Alexander PACHA, Jürgen SCHMIDHUBER und Thilo STADELMANN, 2021. The DeepScoresV2 dataset and benchmark for music object detection. In: 2020 25th International Conference on Pattern Recognition (ICPR). Conference paper. IEEE. 2021. S. 9188–9195. ISBN 978-1-7281-8808-9
Tuggener, Lukas, Yvan Putra Satyawan, Alexander Pacha, Jürgen Schmidhuber, and Thilo Stadelmann. 2021. “The DeepScoresV2 Dataset and Benchmark for Music Object Detection.” Conference paper. In 2020 25th International Conference on Pattern Recognition (ICPR), 9188–95. IEEE. https://doi.org/10.1109/ICPR48806.2021.9412290.
Tuggener, Lukas, et al. “The DeepScoresV2 Dataset and Benchmark for Music Object Detection.” 2020 25th International Conference on Pattern Recognition (ICPR), IEEE, 2021, pp. 9188–95, https://doi.org/10.1109/ICPR48806.2021.9412290.


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