1 code implementation • 15 Mar 2024 • Anton Pelykh, Ozge Mercanoglu Sincan, Richard Bowden
Our approach not only enhances the quality of the generated hands but also offers improved control over hand pose, advancing the capabilities of pose-conditioned human image generation.
no code implementations • 15 Mar 2024 • Ozge Mercanoglu Sincan, Necati Cihan Camgoz, Richard Bowden
Sign Language Translation (SLT) is a challenging task that aims to generate spoken language sentences from sign language videos.
no code implementations • 18 Aug 2023 • Ozge Mercanoglu Sincan, Necati Cihan Camgoz, Richard Bowden
Sign Language Translation (SLT) is a challenging task that aims to generate spoken language sentences from sign language videos, both of which have different grammar and word/gloss order.
no code implementations • 8 Aug 2023 • Harry Walsh, Ozge Mercanoglu Sincan, Ben Saunders, Richard Bowden
As a result, research has turned to TV broadcast content as a source of large-scale training data, consisting of both the sign language interpreter and the associated audio subtitle.
no code implementations • 24 Oct 2021 • Ozge Mercanoglu Sincan, Hacer Yalim Keles
In this paper, we propose an isolated sign language recognition model based on a model trained using Motion History Images (MHI) that are generated from RGB video frames.
no code implementations • 11 May 2021 • Ozge Mercanoglu Sincan, Julio C. S. Jacques Junior, Sergio Escalera, Hacer Yalim Keles
However, several open challenges still need to be solved to allow SLR to be useful in practice.
no code implementations • 3 Aug 2020 • Ozge Mercanoglu Sincan, Hacer Yalim Keles
In AUTSL random train-test splits, our models performed up to 95. 95% accuracy.
Ranked #8 on Sign Language Recognition on AUTSL