Fetching the paper…
Reading the bibliography…
State-of-the-art end-to-end Optical Music Recognition (OMR) has, to date, primarily been carried out using monophonic transcription techniques to handle complex score layouts, such as polyphony, often by resorting to simplifications or specific adaptations.
Huron, D.: Humdrum and kern: Selective feature encoding. Beyond MIDI (1997)
1997
Earlier work this paper cites.
Good, M., Actor, G.: Using MusicXML for file interchange. Web Delivering of Music, International Conference on 0
2003
Earlier work this paper cites.
Graves, A., Fernández, S., Gomez, F., Schmidhuber, J.: Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks. In: Proceedings of the 23rd International Conference on Machine Learning. pp. 369–376. ACM (2006)
2006
Earlier work this paper cites.
Hankinson, A., Roland, P., Fujinaga, I.: The Music Encoding Initiative as a Document-Encoding Framework. Proceedings of the 12th International Society for Music Information Retrieval Conference (2011)
2011
Earlier work this paper cites.
Rebelo, A., Fujinaga, I., Paszkiewicz, F., Marcal, A.R., Guedes, C., Cardoso, J.S.: Optical music recognition: state-of-the-art and open issues. International Journal of Multimedia Information Retrieval 1
2012
Earlier work this paper cites.
Pugin, L., Zitellini, R., Roland, P.: Verovio - A library for Engraving MEI Music Notation into SVG. In: International Society for Music Information Retrieval (jan 2014)
2014
Earlier work this paper cites.
Jan Hajič, j., Pecina, P.: The MUSCIMA++ Dataset for Handwritten Optical Music Recognition. In: 14th International Conference on Document Analysis and Recognition, ICDAR 2017, Kyoto, Japan, November 13 - 15, 2017. pp. 39–46. Dept. of Computer Science and Intelligent Systems, Graduate School of Engineering, Osaka Prefecture University, IEEE Computer Society, New York, USA (2017)
2017
Earlier work this paper cites.
Sapp, C.S.: Verovio humdrum viewer. Proceedings of Music Encoding Conference (MEC), Tours, France (2017)
2017
Earlier work this paper cites.
Shi, B., Bai, X., Yao, C.: An end-to-end trainable neural network for image-based sequence recognition and its application to scene text recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 39
2017
Earlier work this paper cites.
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, L.u., Polosukhin, I.: Attention is all you need. In: Guyon, I., Luxburg, U.V., Bengio, S., Wallach, H., Fergus, R., Vishwanathan, S., Garnett, R. (eds.) Advances in Neural Information Processing Systems. vol. 30. Curran Associates, Inc. (2017)
2017
Earlier work this paper cites.
Zhang, J., Du, J., Zhang, S., Liu, D., Hu, Y., Hu, J., Wei, S., Dai, L.: Watch, attend and parse: An end-to-end neural network based approach to handwritten mathematical expression recognition. Pattern Recognition 71
2017
Earlier work this paper cites.
Calvo-Zaragoza, J., Rizo, D.: End-to-end neural optical music recognition of monophonic scores. Applied Sciences 8
2018
Earlier work this paper cites.
Chiu, C.C., Sainath, T.N., Wu, Y., Prabhavalkar, R., Nguyen, P., Chen, Z., Kannan, A., Weiss, R.J., Rao, K., Gonina, E., Jaitly, N., Li, B., Chorowski, J., Bacchiani, M.: State-of-the-art speech recognition with sequence-to-sequence models. In: 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). pp. 4774–4778 (2018)
2018
Earlier work this paper cites.
Chowdhury, A., Vig, L.: An efficient end-to-end neural model for handwritten text recognition. In: British Machine Vision Conference 2018, BMVC 2018, Newcastle, UK, September 3-6, 2018. p. 202. BMVA Press (2018)
2018
Cited alongside, same era.
McLeod, A., Steedman, M.: Evaluating automatic polyphonic music transcription. In: International Society for Music Information Retrieval Conference (ISMIR). pp. 42–49 (2018)
2018
Cited alongside, same era.
Alfaro-Contreras, M., Calvo-Zaragoza, J., Iñesta, J.M.: Approaching end-to-end optical music recognition for homophonic scores. In: 9th Iberian Conference Pattern Recognition and Image Analysis. Lecture Notes in Computer Science, vol. 11868, pp. 147–158. Springer, Madrid, Spain (2019)
2019
Cited alongside, same era.
Baró, A., Riba, P., Calvo-Zaragoza, J., Fornés, A.: From optical music recognition to handwritten music recognition: A baseline. Pattern Recognition Letters 123
2019
Cited alongside, same era.
Alfaro-Contreras, M., Ríos-Vila, A., Valero-Mas, J.J., Iñesta, J.M., Calvo-Zaragoza, J.: Decoupling music notation to improve end-to-end optical music recognition. Pattern Recognition Letters 158
2022
Later among the works it cites.
Arroyo, V., Valero-Mas, J.J., Calvo-Zaragoza, J., Pertusa, A.: Neural Audio-To-Score Music Transcription For Unconstrained Polyphony Using Compact Output Representations. In: Proceedings of the 47th IEEE International Conference on Acoustics, Speech and Signal Processing. pp. 4603–4607. Singapore, Singapore (2022)
2022
Later among the works it cites.
Baró, A., Riba, P., Fornés, A.: Musigraph: Optical music recognition through object detection and graph neural network. In: International Conference on Frontiers in Handwriting Recognition. pp. 171–184. Springer (2022)
2022
Later among the works it cites.
Kim, G., Hong, T., Yim, M., Nam, J., Park, J., Yim, J., Hwang, W., Yun, S., Han, D., Park, S.: Ocr-free document understanding transformer. In: European Conference on Computer Vision (ECCV) (2022)
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Calvo-Zaragoza, J., Toselli, A.H., Vidal, E.: Handwritten music recognition for mensural notation with convolutional recurrent neural networks. Pattern Recognition Letters 128
2019
Cited alongside, same era.
Foscarin, F., Jacquemard, F., Fournier-S’niehotta, R.: A diff procedure for music score files. In: 6th International Conference on Digital Libraries for Musicology. pp. 58–64 (2019)
2019
Cited alongside, same era.
Román, M.A., Pertusa, A., Calvo-Zaragoza, J.: A Holistic Approach to Polyphonic Music Transcription with Neural Networks. In: Proceedings of the 20th International Society for Music Information Retrieval Conference. pp. 731–737. Delft, The Netherlands (2019)
2019
Cited alongside, same era.
Calvo-Zaragoza, J., Hajič Jr., J., Pacha, A.: Understanding optical music recognition. ACM Comput. Surv. 53
2020
Cited alongside, same era.
Castellanos, F.J., Calvo-Zaragoza, J., Iñesta, J.M.: A neural approach for full-page optical music recognition of mensural documents. In: Proc. of the 21th Int. Society for Music Information Retrieval Conference. pp. 12–16 (2020)
2020
Cited alongside, same era.
Dosovitskiy, A., Beyer, L., Kolesnikov, A., Weissenborn, D., Zhai, X., Unterthiner, T., Dehghani, M., Minderer, M., Heigold, G., Gelly, S., Uszkoreit, J., Houlsby, N.: An image is worth 16x16 words: Transformers for image recognition at scale. In: 9th International Conference on Learning Representations, ICLR 2021, Virtual Event, Austria, May 3-7, 2021. OpenReview.net (2021)
2021
Cited alongside, same era.
Edirisooriya, S., Dong, H.W., Mcauley, J., Berg-Kirkpatrick, T.: An Empirical Evaluation of End-to-End Polyphonic Optical Music Recognition. In: Proceedings of the 22nd International Society for Music Information Retrieval Conference. pp. 167–173. ISMIR (Oct 2021)
2021
Cited alongside, same era.
Singh, S.S., Karayev, S.: Full Page Handwriting Recognition via Image to Sequence Extraction. In: Proceedings of the 16th International Conference on Document Analysis and Recognition. pp. 55–69. Lausanne, Switzerland (2021)
2021
Cited alongside, same era.
2022
Later among the works it cites.
Liu, Z., Mao, H., Wu, C.Y., Feichtenhofer, C., Darrell, T., Xie, S.: A convnet for the 2020s. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 11976–11986 (June 2022)
2022
Later among the works it cites.
Ríos-Vila, A., Iñesta, J.M., Calvo-Zaragoza, J.: On the use of transformers for end-to-end optical music recognition. In: Pattern Recognition and Image Analysis - 10th Iberian Conference, IbPRIA 2022, Aveiro, Portugal, May 4-6, 2022, Proceedings. Lecture Notes in Computer Science, vol. 13256, pp. 470–481. Springer (2022)
2022
Later among the works it cites.
Coquenet, D., Chatelain, C., Paquet, T.: Dan: a segmentation-free document attention network for handwritten document recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 45
2023
Later among the works it cites.
Dhiaf, M., Rouhou, A.C., Kessentini, Y., Salem, S.B.: Msdoctr-lite: A lite transformer for full page multi-script handwriting recognition. Pattern Recognition Letters 169
2023
Later among the works it cites.
Martinez-Sevilla, J.C., Ríos-Vila, A., Castellanos, F.J., Calvo-Zaragoza, J.: A holistic approach for aligned music and lyrics transcription. In: Document Analysis and Recognition - ICDAR 2023 - 17th International Conference, San José, CA, USA, August 21-26, 2023, Proceedings, Part I. Lecture Notes in Computer Science, vol. 14187, pp. 185–201. Springer (2023)
2023
Later among the works it cites.
Ríos-Vila, A., Rizo, D., Iñesta, J.M., Calvo-Zaragoza, J.: End-to-end optical music recognition for pianoform sheet music. Int. J. Document Anal. Recognit. 26
2023
Later among the works it cites.
Torras, P., Biswas, S., Fornés, A.: The common optical music recognition evaluation framework (2023)
2023
Later among the works it cites.
Tuggener, L., Emberger, R., Ghosh, A., Sager, P., Satyawan, Y.P., Montoya, J., Goldschagg, S., Seibold, F., Gut, U., Ackermann, P., et al.: Real world music object recognition (2024)
2024
Closest in time.