Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Sincan, Ozge Mercanoglu"'
Autor:
Cory, Oliver, Sincan, Ozge Mercanoglu, Vowels, Matthew, Battisti, Alessia, Holzknecht, Franz, Tissi, Katja, Sidler-Miserez, Sandra, Haug, Tobias, Ebling, Sarah, Bowden, Richard
Sign Language Assessment (SLA) tools are useful to aid in language learning and are underdeveloped. Previous work has focused on isolated signs or comparison against a single reference video to assess Sign Languages (SL). This paper introduces a nove
Externí odkaz:
http://arxiv.org/abs/2408.10073
Recent years have seen significant progress in human image generation, particularly with the advancements in diffusion models. However, existing diffusion methods encounter challenges when producing consistent hand anatomy and the generated images of
Externí odkaz:
http://arxiv.org/abs/2403.10731
Sign Language Translation (SLT) is a challenging task that aims to generate spoken language sentences from sign language videos. In this paper, we introduce a hybrid SLT approach, Spotter+GPT, that utilizes a sign spotter and a powerful Large Languag
Externí odkaz:
http://arxiv.org/abs/2403.10434
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. From a Neural Machine Translation (NMT) perspective, the strai
Externí odkaz:
http://arxiv.org/abs/2308.09622
Capturing and annotating Sign language datasets is a time consuming and costly process. Current datasets are orders of magnitude too small to successfully train unconstrained \acf{slt} models. As a result, research has turned to TV broadcast content
Externí odkaz:
http://arxiv.org/abs/2308.04248
Sign language recognition using computational models is a challenging problem that requires simultaneous spatio-temporal modeling of the multiple sources, i.e. faces, hands, body, etc. In this paper, we propose an isolated sign language recognition m
Externí odkaz:
http://arxiv.org/abs/2110.12396
The performances of Sign Language Recognition (SLR) systems have improved considerably in recent years. However, several open challenges still need to be solved to allow SLR to be useful in practice. The research in the field is in its infancy in reg
Externí odkaz:
http://arxiv.org/abs/2105.05066
Publikováno v:
IEEE Access (2020), vol. 8, pp. 181340-181355
Sign language recognition is a challenging problem where signs are identified by simultaneous local and global articulations of multiple sources, i.e. hand shape and orientation, hand movements, body posture, and facial expressions. Solving this prob
Externí odkaz:
http://arxiv.org/abs/2008.00932
Publikováno v:
IEEE EUROCON 2015 - International Conference on Computer as a Tool (EUROCON); 2015, p1-6, 6p
