musvit-models

MuSViT — foundation vision model for sheet music (MAESTRO mirror)

Mirror of PRAIG's MuSViT encoders (ECCV 2026), laid out one subdirectory per size for MAESTRO's download-on-demand loader:

Both are standard vit_mae checkpoints (config.json + model.safetensors), byte-identical to upstream (sha256-verified at mirror time). Pre-trained with Masked Autoencoders on 9.7 million sheet-music page images from IMSLP; load through transformers.ViTModel for deterministic page embeddings (1024×1024 input → CLS token).

License — CC BY-NC-SA 4.0 (non-commercial)

These weights are released by PRAIG under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 license and are redistributed here unchanged under the same terms. Non-commercial use only. Attribution: PRAIG (Pattern Recognition and Artificial Intelligence Group, University of Alicante).

Citation

@inproceedings{penarrubia2026musvit,
  title     = {MuSViT: A Foundation Vision Model for Sheet Music Representation},
  author    = {Penarrubia, Carlos and Rios-Vila, Antonio and Fuentes-Martinez, Eliseo
               and Martinez-Sevilla, Juan C. and Castellanos, Francisco J. and
               Alfaro-Contreras, Maria and Calvo-Zaragoza, Jorge},
  booktitle = {European Conference on Computer Vision (ECCV)},
  year      = {2026}
}

The authors acknowledge Edward Guo / IMSLP (Petrucci Music Library) for the training data. Mirrored for MAESTRO by AEmotionStudio.