Papers by Mathieu De Coster

2 papers
Challenges with Sign Language Datasets for Sign Language Recognition and Translation (2022.lrec-1)

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Challenge: Sign Languages are the primary means of communication for at least half a million people in Europe . however, the development of SL recognition and translation tools is slowed down by resource scarcity and data formats are not suitable for machine learning.
Approach: They propose a framework to unify available resources and facilitate SL research for different languages.
Outcome: The proposed framework is based on a set of ELAN files and returns textual and visual data ready to train SL recognition and translation models.
Sign Language Recognition with Transformer Networks (2020.lrec-1)

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Challenge: Sign language recognition is a complex problem, supported by large video corpora . previous work has used feature extraction or end-to-end deep learning to speed annotation .
Approach: They propose to use OpenPose for human keypoint estimation and Convolutional Neural Networks to extract sign language features from video corpora.
Outcome: The proposed method outperforms the state-of-the-art on the Flemish Sign Language corpus.

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