# Learning to Read and Follow Music in Complete Score Sheet Images

arXiv: https://arxiv.org/abs/2007.10736 · HTML: https://mlsanity.com/paper/2007.10736/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Jul 2020.

## Built on by (most cited first, 4 of 4)

- [A Convolutional-Attentional Neural Framework for Structure-Aware Performance-Score Synchronization](https://mlsanity.com/paper/2204.08822/) (2022)
- [Just Label the Repeats for In-The-Wild Audio-to-Score Alignment](https://mlsanity.com/paper/2411.07428/) (2024)
- [Multi-modal Conditional Bounding Box Regression for Music Score Following](https://mlsanity.com/paper/2105.04309/) (2021)
- [Proceedings of the 3rd International Workshop on Reading Music Systems](https://mlsanity.com/paper/2212.00378/) (2022)

## Abstract (arXiv)

This paper addresses the task of score following in sheet music given as unprocessed images. While existing work either relies on OMR software to obtain a computer-readable score representation, or crucially relies on prepared sheet image excerpts, we propose the first system that directly performs score following in full-page, completely unprocessed sheet images. Based on incoming audio and a given image of the score, our system directly predicts the most likely position within the page that matches the audio, outperforming current state-of-the-art image-based score followers in terms of alignment precision. We also compare our method to an OMR-based approach and empirically show that it can be a viable alternative to such a system.