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Found 7 papers, 2 papers with code
Challenges with Sign Language Datasets for Sign Language Recognition and Translation
Furthermore, we propose a framework to address the lack of standardization at format level, unify the available resources and facilitate SL research for different languages.
Sign Language Translation: Ongoing Development, Challenges and Innovations in the SignON Project
The SignON project (www. signon-project. eu) focuses on the research and development of a Sign Language (SL) translation mobile application and an open communications framework.
Towards the extraction of robust sign embeddings for low resource sign language recognition
However, due to a domain mismatch with their training sets and challenging poses in sign language, they lack robustness on sign language data and image-based models often still outperform keypoint-based models.
Machine Translation from Signed to Spoken Languages: State of the Art and Challenges
Automatic translation from signed to spoken languages is an interdisciplinary research domain, lying on the intersection of computer vision, machine translation and linguistics.
Frozen Pretrained Transformers for Neural Sign Language Translation
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.
Isolated Sign Recognition from RGB Video using Pose Flow and Self-Attention
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.
Ranked #6 on
Sign Language Recognition
on AUTSL
Sign Language Recognition with Transformer Networks
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.
