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Institute of Computational Perception
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Matthias Dorfer

Image showing Matthias Dorfer
ASSISTANT

Update: As of April 1, 2019 I am no longer affiliated with the
Institute of Computational Perception at JKU Linz.

Research Interests

  • Reinforcement Learning
  • (Multi-Modality) Deep Learning
  • Audio-Visual Representation Learning
  • Audio Scene Classification

Publications

Cross-Modal Music Retrieval and Applications: An Overview of Key Methodologies.
Meinard Müller, Andreas Arzt, Stefan Balke, Matthias Dorfer and Gerhard Widmer.
IEEE Signal Processing Magazine 36 (1), 52-62

Training General-Purpose Audio Tagging Networks with Noisy Labels and Iterative Self-Verification. (PDF, opens an external URL in a new window, CODE, opens an external URL in a new window, SLIDES, opens an external URL in a new window).
Matthias Dorfer and Gerhard Widmer.
Workshop on Detection and Classification of Acoustic Scenes and Events (DCASE), 2018.
Learning to Listen, Read, and Follow: Score Following as a Reinforcement Learning Game. (PDF, opens an external URL in a new window, CODE, opens an external URL in a new window, VIDEO, opens an external URL in a new window)
Matthias Dorfer, Florian Henkel, and Gerhard Widmer.
In Proceedings of 19th International Society for Music Information Retrieval Conference (ISMIR), 2018.
Best Paper and Best Poster Presentation Award.

Learning Audio-Sheet Music Correspondences for Cross-Modal Retrieval and Piece Identification
(LINK, opens an external URL in a new window, PDF, opens an external URL in a new window, CODE, opens an external URL in a new window)
Matthias Dorfer, Jan Hajič jr., Andreas Arzt, Harald Frostel, and Gerhard Widmer
Transactions of the International Society for Music Information Retrieval, 2018.
Towards Full-Pipeline Handwritten OMR with Musical Symbol Detection by U-Nets
Jan Hajič jr., Matthias Dorfer, Gerhard Widmer, and Pavel Pecina.
In Proceedings of 19th International Society for Music Information Retrieval Conference (ISMIR), 2018.
End-to-End Cross-Modality Retrieval with CCA Projections and Pairwise Ranking Loss (PDF, opens an external URL in a new window, CODE, opens an external URL in a new window).
Matthias Dorfer, Jan Schlüter, Andreu Vall, Filip Korzeniowski and Gerhard Widmer
International Journal of Multimedia Information Retrieval, 2018
A Hybrid Approach to Music Playlist Continuation Based on Playlist-Song Membership
Andreu Vall, Matthias Dorfer, Markus Schedl, and Gerhard Widmer.
In Proceedings of the 33rd Symposium on Applied Computing (SAC), 2018.
Learning Audio-Sheet Music Correspondences for Score Identification and Offline Alignment (PDF, opens an external URL in a new window)
Matthias Dorfer, Andreas Arzt, and Gerhard Widmer.
In Proceedings of 18th International Society for Music Information Retrieval Conference (ISMIR), 2017.
Drum Transcription via Joint Beat and Drum Modeling using Convolutional Recurrent Neural Networks.
Richard Vogl, Matthias Dorfer, Gerhard Widmer and Peter Knees.
In Proceedings of 18th International Society for Music Information Retrieval Conference (ISMIR), 2017.
A Hybrid Approach to Acoustic Scene Classification Based on Multi-channel I-Vectors and Convolutional Neural Networks.
Hamid Eghbal-zadeh, Bernhard Lehner, Matthias Dorfer, and Gerhard Widmer.
In Proceedings of the 25th European Signal Processing Conference (EUSIPCO), 2017.
Music Playlist Continuation by Learning from Hand-Curated Examples and Song Features
Andreu Vall, Hamid Eghbal-zadeh, Matthias Dorfer, Gerhard Widmer and Markus Schedl.
In Proceedings of the 2nd Workshop on Deep Learning for Recommender Systems (DLRS), at the 11th Conference on Recommender Systems (RecSys), 2017.
Drum Transcription from Polyphonic Music with Recurrent Neural Networks.
Richard Vogl, Matthias Dorfer, and Peter Knees.
In Proceedings of 42nd IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017.
Towards Score Following in Sheet Music Images. (PDF, opens an external URL in a new window)
Matthias Dorfer, Andreas Arzt, and Gerhard Widmer.
In Proceedings of 17th International Society for Music Information Retrieval Conference (ISMIR), 2016.
Recurrent Neural Networks for Drum Transcription.
Richard Vogl, Matthias Dorfer and Peter Knees.
In Proceedings of 17th International Society for Music Information Retrieval Conference (ISMIR), 2016.
On the Potential of Simple Framewise Approaches to Piano Transcription.
Rainer Kelz, Matthias Dorfer, Filip Korzeniowski, Sebastian Böck, Andreas Arzt and Gerhard Widmer.
In Proceedings of 17th International Society for Music Information Retrieval Conference (ISMIR), 2016.
Downbeat Estimation from Beat Synchronous Features with Recurrent Neural Networks.
Florian Krebs, Sebastian Böck, Matthias Dorfer and Gerhard Widmer.
In Proceedings of 17th International Society for Music Information Retrieval Conference (ISMIR), 2016.
A Cosine-Distance based Neural Network for Music Artist Recognition using Raw I-vector Features.
Hamid Eghbal-zadeh, Matthias Dorfer and Gerhard Widmer.
In Proceedings of the 19th International Conference on Digital Audio Effects (DAFx16), 2016.
Deep Linear Discriminant Analysis. (PDF, opens an external URL in a new window, CODE, opens an external URL in a new window)
Matthias Dorfer, Rainer Kelz, and Gerhard Widmer.
In Proceedings of the International Conference on Learning Representations (ICLR), 2016.
Recursive Water Flow: A Shape Decomposition Approach for Cell Clump Splitting.
Matthias Dorfer and Julian Mattes.
In Proceedings of the International Symposium on Biomedical Imaging (ISBI), 2016.
Associating approximate paths and temporal sequences of noisy detections: Application to the recovery of spatio-temporal cancer cell trajectories.
Matthias Dorfer, Tomas Kazmar, Matej Smid, Sanchit Sing, Julia Kneißl, Simone Keller, Olivier Debeir, Birgit Luber and Julian Mattes.
Medical Image Analysis, 2016
Creating a large-scale silver corpus from multiple algorithmic segmentations.
Markus Krenn, Matthias Dorfer, Oscar Alfonso Jimenez del Toro, Henning Müller, Bjoern Menze, Marc-Andre Weber, Allan Hanbury and Georg Langs
In MICCAI Workshop on Medical Computer Vision: Algorithms for Big Data, 2015.
Constructing an Un-biased Whole Body Atlas from Clinical Imaging Data by Fragment Bundling.
Matthias Dorfer, René Donner, and Georg Langs
In Proceedings of the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2013.
Robust, Automatic Real-Time Monitoring of the Time Course of the Individual Alpha Frequency in the Time and Frequency Domain.
Heinrich Garn, Markus Waser, Manuel Lechner, Matthias Dorfer, and Dieter Grossegger
In Proceedings of Engineering in Medicine and Biology Society (EMBS), 2012.

Preprints, Workshops and Demonstrations

Attention as a Perspective for Learning Tempo-invariant Audio Queries.
Matthias Dorfer, Jan Hajič jr. and Gerhard Widmer
In ICML 2018 Joint Workshop on Machine Learning for Music, 2018
On the Potential of Fully Convolutional Neural Networks for Musical Symbol Detection.
Matthias Dorfer, Jan Hajič jr. and Gerhard Widmer
In Proceedings of the 12th IAPR International Workshop on Graphics Recognition (GREC), 2017
Prototyping Full-Pipeline Optical Music Recognition with MUSCIMAKRER.
Jan Hajič jr. and Matthias Dorfer
Late Braking Demo at the International Society for Music Information Retrieval Conference (ISMIR), 2017.
Music Playlist Continuation by Learning from Hand-Curated Examples and Song Features: Alleviating the Cold-Start Problem for Rare and Out-of-Set Songs
Andreu Vall, Hamid Eghbal-zadeh, Matthias Dorfer, Markus Schedl, Gerhard Widmer.
In Proceedings of the 2nd Workshop on Deep Learning for Recommender Systems (DLRS), at the 11th Conference on Recommender Systems (RecSys), 2017
Towards End-to-End Audio-Sheet-Music Retrieval.
Matthias Dorfer, Andreas Arzt and Gerhard Widmer.
In NIPS 2016 End-to-end Learning for Speech and Audio Processing Workshop, 2016
Live Score Following on Sheet Music Images.
Matthias Dorfer, Andreas Arzt, Sebastian Böck, Amaury Durand and Gerhard Widmer.
Late Braking Demo at the International Society for Music Information Retrieval Conference (ISMIR), 2016.
Towards Deep and Discriminative Canonical Correlation Analysis.
Matthias Dorfer and Gerhard Widmer.
In ICML 2016 Workshop on Multi-View Representation Learning, 2016.
Timbral and Semantic Features for Music Playlists.
Andreu Vall, Hamid Eghbal-zadeh, Matthias Dorfer and Markus Schedl.
In ICML 2016 Machine Learning for Music Discovery Workshop, 2016.

Challenges

2nd place in the Freesound General-Purpose Audio Tagging Challange, opens an external URL in a new window organized as Task 2 of the 2018 DCASE Challenge, opens an external URL in a new window.
CP-JKU Submission for DCASE-2016: A Hybrid Approach Using Binaural I-Vectors and Deep Convolutional Neural Networks.
Hamid Eghbal-zadeh, Bernhard Lehner, Matthias Dorfer and Gerhard Widmer.
1st and 2nd place winners
Top results in the 2017 AcousticBrainz Genre Task, opens an external URL in a new window at the MediaEval Benchmarking Initiative for Multimedia Evaluation, opens an external URL in a new window.
Khaled Koutini, Alina Imenina, Matthias Dorfer, Alexander Gruber and Markus Schedl
MediaEval Benchmarking Initiative for Multimedia Evaluation, 2017

Invited Talks

Title: Learning Correspondences between Audio and Sheet-Music Images (slides, opens an external URL in a new window)
Matthias Dorfer
Workshop on Systematic Approaches to Deep Learning Methods for Audio, 2017, opens an external URL in a new window

Title: Multi-modal Embedding Space Learning for Cross-Modality Retrieval
Matthias Dorfer
MIC – Machine Learning Talk Series, opens an external URL in a new window, Medical University of Vienna, 2017

Title: Intelligent Music Processing: Artificial Intelligence Meets Music
Andreas Arzt and Matthias Dorfer
Institute of Formal and Applied Linguistics, Charles University, Czech Republic, 2018

Teaching

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Johannes Kepler University Linz

Altenberger Straße 69

4040 Linz, Austria

Telephone +43 732 2468 0
Fax +43 732 2468 4929
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