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Found 7 papers, 1 papers with code
Using an LLM to Turn Sign Spottings into Spoken Language Sentences
Sign Language Translation (SLT) is a challenging task that aims to generate spoken language sentences from sign language videos.
Giving a Hand to Diffusion Models: a Two-Stage Approach to Improving Conditional Human Image Generation
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.
Is context all you need? Scaling Neural Sign Language Translation to Large Domains of Discourse
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.
Gloss Alignment Using Word Embeddings
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.
Using Motion History Images with 3D Convolutional Networks in Isolated Sign Language Recognition
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.
ChaLearn LAP Large Scale Signer Independent Isolated Sign Language Recognition Challenge: Design, Results and Future Research
However, several open challenges still need to be solved to allow SLR to be useful in practice.
AUTSL: A Large Scale Multi-modal Turkish Sign Language Dataset and Baseline Methods
In AUTSL random train-test splits, our models performed up to 95. 95% accuracy.
Ranked #7 on
Sign Language Recognition
on AUTSL
