  The goal of score following is to track a musical performance, usually in the
form of audio, in a corresponding score representation. Established methods
mainly rely on computer-readable scores in the form of MIDI or MusicXML and
achieve robust and reliable tracking results. Recently, multimodal deep
learning methods have been used to follow along musical performances in raw
sheet images. Among the current limits of these systems is that they require a
non trivial amount of preprocessing steps that unravel the raw sheet image into
a single long system of staves. The current work is an attempt at removing this
particular limitation. We propose an architecture capable of estimating
matching score positions directly within entire unprocessed sheet images. We
argue that this is a necessary first step towards a fully integrated score
following system that does not rely on any preprocessing steps such as optical
music recognition.
