Ghent University Academic Bibliography

Journal Article
A1
open access

Signbuddy : from sign language research to scalable co-created solutions

Toon Vandendriessche (UGent) , Caro Brosens, Hannes De Durpel (UGent) , Mathieu De Coster (UGent) and Joni Dambre (UGent)

(2026) UNIVERSAL ACCESS IN THE INFORMATION SOCIETY. 25(2).

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Research Data

Glasses-in-the Wild Dataset

Louis Adriaens (UGent) , Thomas Lips (UGent) , Mathieu De Coster (UGent) , Andreas Verleysen (UGent) and Francis wyffels (UGent)

(2025)

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Miscellaneous
open access

Machine translation from signed to spoken languages : state of the art and challenges (01 Apr, 10.1007/s10209-023-00992-1, 2023)

Mathieu De Coster (UGent) , Dimitar Shterionov, Mieke Van Herreweghe (UGent) and Joni Dambre (UGent)

(2025) UNIVERSAL ACCESS IN THE INFORMATION SOCIETY. In 24 1. p.953-957

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Journal Article
A1
open access

SPILL : size, pose, and internal liquid level estimation of transparent glassware for robotic bartending

Louis Adriaens (UGent) , Thomas Lips (UGent) , Mathieu De Coster (UGent) , Andreas Verleysen (UGent) and Francis wyffels (UGent)

(2025) IEEE ROBOTICS AND AUTOMATION LETTERS. 10(12). p.13288-13295

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Predicting errors and failures in human-robot interaction from multi-modal temporal data

Ruben Janssens (UGent) , Eva Verhelst (UGent) and Mathieu De Coster (UGent)

(2024) PROCEEDINGS OF THE 26TH INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION, ICMI 2024. p.671-676

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Book Chapter

Language resources for European sign languages

Vincent Vandeghinste, Mirella De Sisto, Maria Kopf, Marc Schulder, Caro Brosens, Lien Soetemans (UGent) , Rehana Omardeen, Frankie Picron, Davy Van Landuyt, Irene Murtagh, et al.

(2024) Sign language machine translation. In Machine translation : technologies and applications 5. p.141-170

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Book Chapter

Sign languages as source language for machine translation : historical overview and challenges

Joni Dambre (UGent) and Mathieu De Coster (UGent)

(2024) Sign language machine translation. In Machine translation : technologies and applications 5. p.171-198

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Book Chapter

Challenges with sign language datasets

Vincent Vandeghinste, Mirella De Sisto, Santiago Egea Gómez and Mathieu De Coster (UGent)

(2024) Sign language machine translation. In Machine translation : technologies and applications 5. p.117-139

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PhD Thesis
open access

Neural sign language recognition and translation : towards sign language applications powered by artificial intelligence

Mathieu De Coster (UGent)

(2024)

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Journal Article
A1
open access

Machine translation from signed to spoken languages : state of the art and challenges

Mathieu De Coster (UGent) , Dimitar Shterionov, Mieke Van Herreweghe (UGent) and Joni Dambre (UGent)

(2024) UNIVERSAL ACCESS IN THE INFORMATION SOCIETY. 23(3). p.1305-1331

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Conference Paper
C1
open access

Trends and challenges for sign language recognition with machine learning

J. Fink, Mathieu De Coster (UGent) , Joni Dambre (UGent) and B. Frénay

(2023) ESANN 2023, 31st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Proceedings. p.561-570

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Conference Paper
P1
open access

From scarcity to understanding : transfer learning for the extremely low resource Irish sign language

R. Holmes, E. Rushe, Mathieu De Coster (UGent) , Maxim Bonnaerens, S. Satoh, A. Sugimoto and A. Ventresque

(2023) 2023 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS, ICCVW. In IEEE International Conference on Computer Vision Workshops p.2000-2009

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Conference Paper
C1
open access

SignON : sign language translation : progress and challenges

Vincent Vandeghinste, Dimitar Shterionov, Mirella De Sisto, Aoife Brady, Mathieu De Coster (UGent) , Lorraine Leeson, Josep Blat, Frankie Picron, Marcello Paolo Scipioni, Aditya Parikh, et al.

(2023) Proceedings of the 24th Annual Conference of the European Association for Machine Translation. p.501-502

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Conference Paper
P1
open access

Querying a sign language dictionary with videos using dense vector search

Mathieu De Coster (UGent) and Joni Dambre (UGent)

(2023) 2023 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING WORKSHOPS, ICASSPW.

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Conference Paper
C1
open access

Sign language translation : ongoing development, challenges and innovations in the SignON project

Dimitar Shterionov, Mirella De Sisto, Vincent Vandeghinste, Aoife Brady, Mathieu De Coster (UGent) , Lorraine Leeson, Josep Blat, Frankie Picron, Marcello Scipioni, Aditya Parikh, et al.

(2022) Proceedings of the 23rd Annual Conference of the European Association for Machine Translation. p.325-326

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Conference Paper
P1
open access

Challenges with sign language datasets for sign language recognition and translation

Mirella De Sisto, Vincent Vandeghinste, Santiago Egea Gomez, Mathieu De Coster (UGent) , Dimitar Shterionov and Horacio Saggion

(2022) PROCEEDINGS OF THE 13TH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION (LREC 2022). In LREC Proceedings p.2478-2487

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Conference Paper
C3
open access

A corpus for training sign language recognition and translation : the Belgian federal COVID-19 video corpus

Vincent Vandeghinste, Bob Van Dyck, Mathieu De Coster (UGent) and Maud Goddefroy

(2022) 32nd Meeting of Computational Linguistics in The Netherlands, Abstracts.

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Conference Paper
C3
open access

Progress, challenges and innovations of the SignON project

Vincent Vandeghinste, Mirella De Sisto, Dimitar Shterionov, Aoife Brady, Mathieu De Coster (UGent) , Lorraine Leeson, Josep Blat, Frankie Picron, Marcello Scipioni, Aditya Parikh, et al.

(2022) 32nd Meeting of Computational Linguistics in The Netherlands, Abstracts.

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Conference Paper
C3
open access

Attention analysis of a sign language recognition task on the AUTSL dataset

Jeanne Coppin, Mathieu De Coster (UGent) and Joni Dambre (UGent)

(2022) 32nd Meeting of Computational Linguistics in The Netherlands, Abstracts.

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Journal Article
A2
open access

Leveraging frozen pretrained written language models for neural sign language translation

Mathieu De Coster (UGent) and Joni Dambre (UGent)

(2022) INFORMATION. 13(5).

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Journal Article
A2
open access

BeCoS corpus : Belgian Covid-19 Sign language corpus : a corpus for training sign language recognition and translation

Vincent Vandeghinste, Bob Van Dyck, Mathieu De Coster (UGent) , Maud Goddefroy and Joni Dambre (UGent)

(2022) COMPUTATIONAL LINGUISTICS IN THE NETHERLANDS JOURNAL. 12. p.7-17

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Conference Paper
C1
open access

Frozen pretrained transformers for neural sign language translation

Mathieu De Coster (UGent) , Karel D'Oosterlinck (UGent) , Marija Pizurica (UGent) , Paloma Rabaey (UGent) , Severine Verlinden, Mieke Van Herreweghe (UGent) and Joni Dambre (UGent)

(2021) Proceedings of the 1st International Workshop on Automatic Translation for Signed and Spoken Languages (AT4SSL). p.88-97

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Conference Paper
C3
open access

The SignON project : a sign language translation framework

Dimitar Shterionov, Vincent Vandeghinste, Horacio Saggion, Josep Blat, Mathieu De Coster (UGent) , Joni Dambre (UGent) , Henk van den Heuvel, Irene Murtagh, Lorraine Leeson and Ineke Schuurman

(2021) 31st Meeting of Computational Linguistics in The Netherlands, Abstracts.

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Conference Paper
P1
open access

Isolated sign recognition from RGB video using pose flow and self-attention

Mathieu De Coster (UGent) , Mieke Van Herreweghe (UGent) and Joni Dambre (UGent)

(2021) 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). In IEEE Computer Society Conference on Computer Vision and Pattern Recognition workshops p.3441-3450

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Conference Paper
P1
open access

Sign language recognition with transformer networks

Mathieu De Coster (UGent) , Mieke Van Herreweghe (UGent) and Joni Dambre (UGent)

(2020) PROCEEDINGS OF THE 12TH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION (LREC 2020). p.6018-6024

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Towards automatic sign language corpus annotation using deep learning

Mathieu De Coster (UGent) , Mieke Van Herreweghe (UGent) and Joni Dambre (UGent)

(2019) 6th Workshop on Sign Language Translation and Avatar Technology (SLTAT).

Academic Bibliography

Signbuddy : from sign language research to scalable co-created solutions

Glasses-in-the Wild Dataset

Machine translation from signed to spoken languages : state of the art and challenges (01 Apr, 10.1007/s10209-023-00992-1, 2023)

SPILL : size, pose, and internal liquid level estimation of transparent glassware for robotic bartending

Predicting errors and failures in human-robot interaction from multi-modal temporal data

Language resources for European sign languages

Sign languages as source language for machine translation : historical overview and challenges

Challenges with sign language datasets

Neural sign language recognition and translation : towards sign language applications powered by artificial intelligence

Machine translation from signed to spoken languages : state of the art and challenges

Trends and challenges for sign language recognition with machine learning

From scarcity to understanding : transfer learning for the extremely low resource Irish sign language

SignON : sign language translation : progress and challenges

Querying a sign language dictionary with videos using dense vector search

Sign language translation : ongoing development, challenges and innovations in the SignON project

Challenges with sign language datasets for sign language recognition and translation

A corpus for training sign language recognition and translation : the Belgian federal COVID-19 video corpus

Progress, challenges and innovations of the SignON project

Attention analysis of a sign language recognition task on the AUTSL dataset

Leveraging frozen pretrained written language models for neural sign language translation

BeCoS corpus : Belgian Covid-19 Sign language corpus : a corpus for training sign language recognition and translation

Frozen pretrained transformers for neural sign language translation

The SignON project : a sign language translation framework

Isolated sign recognition from RGB video using pose flow and self-attention

Sign language recognition with transformer networks

Towards automatic sign language corpus annotation using deep learning

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