Search Results for author: Mieke Van Herreweghe

Found 5 papers, 3 papers with code

Machine Translation from Signed to Spoken Languages: State of the Art and Challenges

no code implementations7 Feb 2022 Mathieu De Coster, Dimitar Shterionov, Mieke Van Herreweghe, Joni Dambre

Automatic translation from signed to spoken languages is an interdisciplinary research domain, lying on the intersection of computer vision, machine translation and linguistics.

Machine Translation Sign Language Translation +1

Frozen Pretrained Transformers for Neural Sign Language Translation

1 code implementation International Workshop on Automatic Translation for Signed and Spoken Languages (AT4SSL) 2021 Mathieu De Coster, Karel D'Oosterlinck, Marija Pizurica, Paloma Rabaey, Severine Verlinden, Mieke Van Herreweghe, Joni Dambre

Our results show that pretrained language models can be used to improve sign language translation performance and that the self-attention patterns in BERT transfer in zero-shot to the encoder and decoder of sign language translation models.

Decoder Machine Translation +3

Isolated Sign Recognition from RGB Video using Pose Flow and Self-Attention

1 code implementation Computer Vision and Pattern Recognition Workshops (CVPRW) 2021 Mathieu De Coster, Mieke Van Herreweghe, Joni Dambre

However, due to the limited amount of labeled data that is commonly available for training automatic sign (language) recognition, the VTN cannot reach its full potential in this domain.

Action Recognition Sign Language Recognition +1

Sign Language Recognition with Transformer Networks

no code implementations LREC 2020 Mathieu De Coster, Mieke Van Herreweghe, Joni Dambre

Sign language recognition can be used to speed up the annotation process of these corpora, in order to aid research into sign languages and sign language recognition.

Keypoint Estimation Sign Language Recognition

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