# Tipiano: Cascaded Piano Hand Motion Synthesis via Fingertip Priors

Source: [Tipiano: Cascaded Piano Hand Motion Synthesis via Fingertip Priors](<https://www.sota2.com/research/paper/69ddca047d0172140ec79936>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-04-15T05:00:04.591Z

Authors: Joonhyung Bae, Kirak Kim, Hyeyoon Cho, Sein Lee, Yoon-Seok Choi, Hyeon Hur, Gyubin Lee, Akira Maezawa, Satoshi Obata, Jonghwa Park, Jaebum Park, Juhan Nam

Published: 2026-04-06T15:04:23.000Z

## Abstract

Synthesizing realistic piano hand motions requires both precision and naturalness. Physics-based methods achieve precision but produce stiff motions; data-driven models learn natural dynamics but struggle with positional accuracy. Piano motion exhibits a natural hierarchy: fingertip positions are nearly deterministic given piano geometry and fingering, while wrist and intermediate joints offer stylistic freedom. We present \[OURS\], a four-stage framework exploiting this hierarchy: (1) statistics-based fingertip positioning, (2) FiLM-conditioned trajectory refinement, (3) wrist estimation, and (4) STGCN-based pose synthesis. We contribute expert-annotated fingerings for the F\\"urElise dataset (153 pieces, ~10 hours). Experiments demonstrate F1 = 0.910, substantially outperforming diffusion baselines (F1 = 0.121), with user study (N=41) confirming quality approaching motion capture. Expert evaluation by professional pianists (N=5) identified anticipatory motion as the key remaining gap, providing concrete directions for future improvement.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [Piano Key Contact Prediction on FürElise Dataset (test)](<https://www.sota2.com/research/sota/piano-key-contact-prediction-on-f-relise-dataset-test.md>): Piano Key Contact Prediction; FürElise Dataset (test); Precision: 84.3.

- [Piano Playing Motion Generation on FürElise Dataset (test)](<https://www.sota2.com/research/sota/piano-playing-motion-generation-on-f-relise-dataset-test.md>): Piano Playing Motion Generation; FürElise Dataset (test); Position Error (mm) Fingertip Left: 37.4.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2604.09692>)

[PDF](<https://arxiv.org/pdf/2604.09692.pdf>)