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This GitHub repository contains the implementation of the Sheet Music Transformer ++ (SMT), the upgraded version of the Sheet Music Transformer model for full-page pianoform music sheet transcription. Unlike traditional approaches that primarily resort this challenge by implementing layout analysis techniques with end-to-end transcription, the SMT ++ model offers a image-to-sequence solution for transcribing these scores directly from images. To do so, this model is trained through a progressive curriculum learning strategy with synthetic generation.
Usage instructions and data publication coming (hopefully) soon!
@misc{RiosVila:2024:SMTplusplus,
title={Sheet Music Transformer ++: End-to-End Full-Page Optical Music Recognition for Pianoform Sheet Music},
author={Antonio Ríos-Vila and Jorge Calvo-Zaragoza and David Rizo and Thierry Paquet},
year={2024},
eprint={2405.12105},
archivePrefix={arXiv},
primaryClass={cs.CV}
}